April 20, 2014

Spreading .ibd files across multiple disks; the optimization that isn’t

Inspired by Baron’s earlier post, here is one I hear quite frequently – “If you enable innodb_file_per_table, each table is it’s own .ibd file.  You can then relocate the heavy hit tables to a different location and create symlinks to the original location.” There are a few things wrong with this advice:

Lost innodb tables, xfs and binary grep

Before I start a story about the data recovery case I worked on yesterday, here’s a quick tip – having a database backup does not mean you can restore from it. Always verify your backup can be used to restore the database! If not automatically, do this manually, at least once a month. No, seriously […]

An argument for not using mysqldump

I have a 5G mysqldump which takes 30 minutes to restore from backup.  That means that when the database reaches 50G, it should take 30×10=5 hours to restore.  Right?  Wrong.

Sharing an auto_increment value across multiple MySQL tables

The title is SEO bait – you can’t do it. We’ve seen a few recurring patterns trying to achieve similar – and I thought I would share with you my favorite two: Option #1: Use a table to insert into, and grab the insert_id:

Option #2: Use a table with one just row:

Instrumentation and the cost of Foreign Keys

I occasionally get in to light arguments healthy discussions with students about whether or not to use Foreign Key constraints on InnoDB tables.  My standard response has always been: “it depends on how much of a tradeoff you are willing to make for performance. In some situations the cost can be considerable”. .. that’s when […]

UDF -vs- MySQL Stored Function

Few days ago I was working on a case where we needed to modify a lot of data before pushing it to sphinx – MySQL did not have a function to do the thing so I thought I’ll write MySQL Stored Function and we’ll be good to go. It worked! But not so well really […]

Why message queues and offline processing are so important

If you read Percona’s whitepaper on Goal-Driven Performance Optimization, you will notice that we define performance using the combination of three separate terms. You really want to read the paper, but let me summarize it here: Response Time – This is the time required to complete a desired task. Throughput – Throughput is measured in […]

Caching could be the last thing you want to do

I recently had a run-in with a very popular PHP ecommerce package which makes me want to voice a recurring mistake I see in how many web applications are architected. What is that mistake? The ecommerce package I was working with depended on caching.  Out of the box it couldn’t serve 10 pages/second unless I […]

EXPLAIN EXTENDED can tell you all kinds of interesting things

While many people are familiar with the MySQL EXPLAIN command, fewer people are familiar with “extended explain” which was added in MySQL 4.1 EXPLAIN EXTENDED can show you what the MySQL optimizer does to your query. You might not know this, but MySQL can dramatically change your query before it actually executes it. This process […]

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 […]