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 [...]
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: [...]
Connecting orphaned .ibd files
May 13, 2011 By 19 Comments
There are two ways InnoDB can organize tablespaces. First is when all data, indexes and system buffers are stored in a single tablespace. This is typicaly one or several ibdata files. A well known innodb_file_per_table option brings the second one. Tables and system areas are split into different files. Usually system tablespace is located in [...]
Shard-Query EC2 images available
May 11, 2011 By 2 Comments
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 [...]
Innodb Caching (part 2)
May 10, 2011 By 7 Comments
Few weeks ago I wrote about Innodb Caching with main idea you might need more cache when you think you are because Innodb caches data in pages, not rows, and so the whole page needs to be in memory even if you need only one row from it. I have created the simple benchmark which [...]
Shard-Query turbo charges Infobright community edition (ICE)
May 6, 2011 By 23 Comments
Shard-Query is an open source tool kit which helps improve the performance of queries against a MySQL database by distributing the work over multiple machines and/or multiple cores. This is similar to the divide and conquer approach that Hive takes in combination with Hadoop. Shard-Query applies a clever approach to parallelism which allows it to [...]
The two even more fundamental performance metrics
May 5, 2011 By 6 Comments
In a recent blog post, I wrote about four fundamental metrics for system performance analysis. These are throughput, residence time, “weighted time” (the sum of all residence times in the observation period — the terminology is mine for lack of a better name), and concurrency. I derived all of these metrics from two “even more [...]
Using Flexviews – part one, introduction to materialized views
March 23, 2011 By 3 Comments
If you know me, then you probably have heard of Flexviews. If not, then it might not be familiar to you. I’m giving a talk on it at the MySQL 2011 CE, and I figured I should blog about it before then. For those unfamiliar, Flexviews enables you to create and maintain incrementally refreshable materialized [...]
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 [...]
Scaling: Consider both Size and Load
July 13, 2010 By 5 Comments
So lets imagine you have the server handling 100.000 user accounts. You can see the CPU,IO and Network usage is below 10% of capacity – does it mean you can count on server being able to handle 1.000.000 of accounts ? Not really, and there are few reasons why, I’ll name most important of them: [...]
