July 26, 2014

Benchmarking single-row insert performance on Amazon EC2

I have been working for a customer benchmarking insert performance on Amazon EC2, and I have some interesting results that I wanted to share. I used a nice and effective tool iiBench which has been developed by Tokutek. Though the “1 billion row insert challenge” for which this tool was originally built is long over, […]

Avoiding auto-increment holes on InnoDB with INSERT IGNORE

Are you using InnoDB tables on MySQL version 5.1.22 or newer? If so, you probably have gaps in your auto-increment columns. A simple INSERT IGNORE query creates gaps for every ignored insert, but this is undocumented behaviour. This documentation bug is already submitted. Firstly, we will start with a simple question. Why do we have […]

Improved InnoDB fast index creation

One of the serious limitations in the fast index creation feature introduced in the InnoDB plugin is that it only works when indexes are explicitly created using ALTER TABLE or CREATE INDEX. Peter has already blogged about it before, here I’ll just briefly reiterate other cases that might benefit from that feature: when ALTER TABLE […]

Dynamic row format for MEMORY tables

The latest Percona Server release has one new feature: now MEMORY tables can have BLOB and TEXT columns, and VARCHAR columns will not waste space due to implicit extension to CHAR.

Using any general purpose computer as a special purpose SIMD computer

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 […]

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 […]

Flexviews – part 3 – improving query performance using materialized views

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 […]

Using Flexviews – part two, change data capture

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 […]

Extending Index for Innodb tables can hurt performance in a surprising way

One schema optimization we often do is extending index when there are queries which can use more key part. Typically this is safe operation, unless index length increases dramatically queries which can use index can also use prefix of the new index are they ? It turns there are special cases when this is not […]

A workaround for the performance problems of TEMPTABLE views

MySQL supports two different algorithms for views: the MERGE algorithm and the TEMPTABLE algorithm. These two algorithms differ greatly. A view which uses the MERGE algorithm can merge filter conditions into the view query itself. This has significant performance advantages over TEMPTABLE views. A view which uses the TEMPTABLE algorithm will have to compute the […]