April 24, 2014

Investigating MySQL Replication Latency in Percona XtraDB Cluster

I was curious to check how Percona XtraDB Cluster behaves when it comes to MySQL replication latency — or better yet, call it data propagation latency. It was interesting to see whenever I can get stale data reads from other cluster nodes after write performed to some specific node. To test it I wrote quite a […]

Wow. My 6 year old MySQL Bug is finally fixed in MySQL 5.6

I got the message in the morning today about the bug being fixed in MySQL 5.6.6…. which I reported in Early 2006 (while still being with MySQL) and running MySQL 4.1 I honestly thought this issue was fixed long ago as it was indeed pretty annoying. I must say I’m very impressed with Oracle team […]

Side load may massively impact your MySQL Performance

When we’re looking at benchmarks we typically run some stable workload and we run it in isolation – nothing else is happening on the system. This is not however how things happen in real world when we have significant variance in the load and many things can be happening concurrently. It is very typical to […]

Shard-Query turbo charges Infobright community edition (ICE)

Shard-Query is an open source tool kit which helps improve the performance of queries against a MySQL database by distributing the work over multiple machines and/or multiple cores. This is similar to the divide and conquer approach that Hive takes in combination with Hadoop. Shard-Query applies a clever approach to parallelism which allows it to […]

Should we give a MySQL Query Cache a second chance ?

Over last few years I’ve been suggesting more people to disable Query Cache than to enable it. It can cause contention problems as well as stalls and due to coarse invalidation is not as efficient as it could be. These are however mostly due to neglect Query Cache received over almost 10 years, with very […]

MySQL caching methods and tips

“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding […]

The Doom of Multiple Storage Engines

One of the big “Selling Points” of MySQL is support for Multiple Storage engines, and from the glance view it is indeed great to provide users with same top level SQL interface allowing them to store their data many different way. As nice as it sounds the in theory this benefit comes at very significant […]

How to generate per-database traffic statistics using mk-query-digest

We often encounter customers who have partitioned their applications among a number of databases within the same instance of MySQL (think application service providers who have a separate database per customer organization … or wordpress-mu type of apps). For example, take the following single MySQL instance with multiple (identical) databases:

How much memory can MySQL use in the worst case?

I vaguely recall a couple of blog posts recently asking something like “what’s the formula to compute mysqld’s worst-case maximum memory usage?” Various formulas are in wide use, but none of them is fully correct. Here’s why: you can’t write an equation for it.

Using Multiple Key Caches for MyISAM Scalability

I have written before – MyISAM Does Not Scale, or it does quite well – two main things stopping you is table locks and global mutex on the KeyCache. Table Locks are not the issue for Read Only workload and write intensive workloads can be dealt with by using with many tables but Key Cache […]