September 21, 2014

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 […]

Just do the math!

One of the most typical reasons for performance and scalability problems I encounter is simply failing to do the math. And these are typically bad one because it often leads to implementing architectures which are not up for job they are intended to solve. Let me start with example to make it clear. Lets say […]

Missing Data – rows used to generate result set

As Baron writes it is not the number of rows returned by the query but number of rows accessed by the query will most likely be defining query performance. Of course not all row accessed are created equal (such as full table scan row accesses may be much faster than random index lookups row accesses […]

GROUP_CONCAT useful GROUP BY extension

(There is an updated version of this post here) MySQL has useful extention to the GROUP BY operation: function GROUP_CONCAT: GROUP_CONCAT(expr) – This function returns a string result with the concatenated non-NULL values from a group. Where it can be useful?