October 31, 2014

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 […]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see http://www.percona.com/blog/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron’s example I also run the same load against MonetDB. Reading comments to Baron’s post I tied to load the same data to LucidDB, but I was not successful in this. I tried to analyze a bigger dataset and I took public […]

High-Performance Click Analysis with MySQL

We have a lot of customers who do click analysis, site analytics, search engine marketing, online advertising, user behavior analysis, and many similar types of work.  The first thing these have in common is that they’re generally some kind of loggable event. The next characteristic of a lot of these systems (real or planned) is […]

JOIN Performance & Charsets

We have written before about the importance of using numeric types as keys, but maybe you’ve inherited a schema that you can’t change or have chosen string types as keys for a specific reason. Either way, the character sets used on joined columns can have a significant impact on the performance of your queries. Take […]

Enum Fields VS Varchar VS Int + Joined table: What is Faster?

Really often in customers’ application we can see a huge tables with varchar/char fields, with small sets of possible values. These are “state”, “gender”, “status”, “weapon_type”, etc, etc. Frequently we suggest to change such fields to use ENUM column type, but is it really necessary (from performance standpoint)? In this post I’d like to present […]

Be careful when joining on CONCAT

The other day I had a case with an awful performance of a rather simple join. It was a join on tb1.vid = CONCAT(‘prefix-‘, tb2.id) with tb1.vid – indexed varchar(100) and tb2.id – int(11) column. No matter what I did – forced it to use key, forced a different join order, it did not want […]

Using CHAR keys for joins, how much is the overhead ?

I prefer to use Integers for joins whenever possible and today I worked with client which used character keys, in my opinion without a big need. I told them this is suboptimal but was challenged with rightful question about the difference. I did not know so I decided to benchmark. The results below are for […]

Using delayed JOIN to optimize count(*) and LIMIT queries

In many Search/Browse applications you would see main (fact) table which contains search fields and dimension tables which contain more information about facts and which need to be joined to get query result. If you’re executing count(*) queries for such result sets MySQL will perform the join even if you use LEFT JOIN so it […]

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 […]

Innodb row size limitation

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.