May 23, 2013

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 [...]

Joining on range? Wrong!

The problem I am going to describe is likely to be around since the very beginning of MySQL, however unless you carefully analyse and profile your queries, it might easily go unnoticed. I used it as one of the examples in our talk given at phpDay.it conference last week to demonstrate some pitfalls one may [...]

PROCEDURE ANALYSE

Quite common task during schema review is to find the optimal data type for the column value – for example column is defined as INT but is it really needed or may be SMALLINT or even TINYINT will do instead. Does it contain any NULLs or it can be defined NOT NULL which reduces space [...]

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 [...]

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 [...]

To SQL_CALC_FOUND_ROWS or not to SQL_CALC_FOUND_ROWS?

When we optimize clients’ SQL queries I pretty often see a queries with SQL_CALC_FOUND_ROWS option used. Many people think, that it is faster to use this option than run two separate queries: one – to get a result set, another – to count total number of rows. In this post I’ll try to check, is [...]

PBXT benchmarks

The PBXT Storage Engine (http://www.primebase.com/xt/) is getting stable and we decided to benchmark it in different workloads. This time I tested only READ queries, similar to ones in benchmark InnoDB vs MyISAM vs Falcon (http://www.mysqlperformanceblog.com/2007/01/08/innodb-vs-myisam-vs-falcon-benchmarks-part-1) The difference is I used new sysbench with Lua scripting language, so all queries were scripted for sysbench.

InnoDB vs MyISAM vs Falcon benchmarks – part 1

Several days ago MySQL AB made new storage engine Falcon available for wide auditory. We cannot miss this event and executed several benchmarks to see how Falcon performs in comparison to InnoDB and MyISAM. The second goal of benchmark was a popular myth that MyISAM is faster than InnoDB in reads, as InnoDB is transactional, [...]

Long PRIMARY KEY for Innodb tables

I’ve written and spoke a lot about using short PRIMARY KEYs with Innodb tables due to the fact all other key will refer to the rows by primary key. I also recommended to use sequential primary keys so you do not end up having random primary key BTREE updates which can be very expensive. Today [...]