DELETE IGNORE suppresses errors and downgrades them as warnings, if you are not aware how IGNORE behaves on tables with FOREIGN KEYs, you could be in for a surprise. Let’s take a table with data as example, column c1 on table t2 references column c1 on table t1 – both columns have identical set of rows for [...]
Percona testing: Quick test clusters with kewpie!
January 13, 2012 By Leave a Comment
The announcement of Percona XtraDB Cluster seems to have generated a fair bit of interest : ) Although the documentation contains more formal instructions for setting up a test cluster, I wanted to share a quick way to set up an ad-hoc cluster on a single machine to help people play with this (imho) rather [...]
Avoiding auto-increment holes on InnoDB with INSERT IGNORE
November 29, 2011 By 8 Comments
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
November 6, 2011 By 4 Comments
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
September 6, 2011 By 5 Comments
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.
Checking the subset sum set problem with set processing
May 16, 2011 By Leave a Comment
Hi, Here is an easy way to run the subset sum check from SQL, which you can then distribute with Shard-Query:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | CREATE TABLE `the list` ( `id` bigint(20) NOT NULL AUTO_INCREMENT, `val` bigint(20) NOT NULL DEFAULT '0', PRIMARY KEY (`id`), KEY `id` (`id`) ) ENGINE=MyISAM; SELECT val as `val`, COUNT(DISTINCT (id)) as `cd` FROM test.data as d WHERE val in (-2,-3,-10,15,15,16) GROUP BY val; +-----+----------+----------+ | val | cd | CNT | +-----+----------+----------+ | -10 | 1 | 1 | | -3 | 1 | 1 | | -2 | 1 | 1 | | 15 | 35417088 | 35417088 | +-----+----------+----------+ 5 rows in set (40.20 sec) |
Notice there is no 16 in the list. We did not pass the check. There are enough 15s though. The distinct value count for each item in the output set, must at least [...]
Using any general purpose computer as a special purpose SIMD computer
May 16, 2011 By 5 Comments
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
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 row size limitation
April 7, 2011 By 12 Comments
I recently worked on a customer case where at seemingly random times, inserts would fail with Innodb error 139. This is a rather simple problem, but due to it’s nature, it may only affect you after you already have a system running in production for a while.
Flexviews – part 3 – improving query performance using materialized views
April 4, 2011 By 20 Comments
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 [...]
