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
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 [...]
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 [...]
MySQL caching methods and tips
April 4, 2011 By 5 Comments
“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 [...]
Is VoltDB really as scalable as they claim?
February 28, 2011 By 3 Comments
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 [...]
MySQL Limitations Part 4: One thread per connection
October 27, 2010 By 14 Comments
This is the third in a series on what’s seriously limiting MySQL in core use cases (links: part 1, 2, 3). This post is about the way MySQL handles connections, allocating one thread per connection to the server.
Intro to OLAP
July 12, 2010 By 10 Comments
This is the first of a series of posts about business intelligence tools, particularly OLAP (or online analytical processing) tools using MySQL and other free open source software. OLAP tools are a part of the larger topic of business intelligence, a topic that has not had a lot of coverage on MPB. Because of this, [...]
Pacemaker, please meet NDB Cluster or using Pacemaker/Heartbeat to start a NDB Cluster
May 19, 2010 By 10 Comments
Customers have always asked me to make NDB Cluster starts automatically upon startup of the servers. For the ones who know NDB Cluster, it is tricky to make it starts automatically. I know at least 2 sets of scripts to manage NDB startup, ndb-initializer and from Johan configurator www.severalnines.com. If all the nodes come up [...]
Why you should ignore MySQL’s key cache hit ratio
February 28, 2010 By 28 Comments
I have not caused a fist fight in a while, so it’s time to take off the gloves. I claim that somewhere around of 99% of advice about tuning MySQL’s key cache hit ratio is wrong, even when you hear it from experts. There are two major problems with the key buffer hit ratio, and [...]
How much memory can MySQL use in the worst case?
February 12, 2009 By 17 Comments
I vaguely recall a couple of blog posts recently asking something like “what’s the formula to compute mysqld’s worst-case maximum memory usage?” Various formulas are in wide use, but none of them is fully correct. Here’s why: you can’t write an equation for it.
