October 21, 2014

MySQL Partitioning – can save you or kill you

I wanted for a while to write about using MySQL Partitioning for Performance Optimization and I just got a relevant customer case to illustrate it. First you need to understand how partitions work internally. Partitions are on the low level are separate table. This means when you’re doing lookup by partitioned key you will look […]

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 […]

How number of columns affects performance ?

It is pretty understood the tables which have long rows tend to be slower than tables with short rows. I was interested to check if the row length is the only thing what matters or if number of columns we have to work with also have an important role. I was interested in peak row […]

Multi Column indexes vs Index Merge

The mistake I commonly see among MySQL users is how indexes are created. Quite commonly people just index individual columns as they are referenced in where clause thinking this is the optimal indexing strategy. For example if I would have something like AGE=18 AND STATE=’CA’ they would create 2 separate indexes on AGE and STATE […]

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 […]

Duplicate indexes and redundant indexes

About every second application I look at has some tables which have redundant or duplicate indexes so its the time to speak about these a bit. So what is duplicate index ? This is when table has multiple indexes defined on the same columns. Sometimes it is indexes with different names, sometimes it is different […]

Cache Performance Comparison

Jay Pipes continues cache experiements and has compared performance of MySQL Query Cache and File Cache. Jay uses Apache Benchmark to compare full full stack, cached or not which is realistic but could draw missleading picture as contribution of different components may be different depending on your unique applications. For example for application containing a […]