September 17, 2014

3 ways MySQL uses indexes

I often see people confuse different ways MySQL can use indexing, getting wrong ideas on what query performance they should expect. There are 3 main ways how MySQL can use the indexes for query execution, which are not mutually exclusive, in fact some queries will use indexes for all 3 purposes listed here.

When would you use SAN with MySQL ?

One question which comes up very often is when one should use SAN with MySQL, which is especially popular among people got used to Oracle or other Enterprise database systems which are quite commonly deployed on SAN. My question in such case is always what exactly are you trying to get by using SAN ?

What would make MySQL Multiple Queries Usable ?

MySQL Has API to run Multiple Queries at once. This feature was designed mainly with saving network round trip in mind and got a little traction due to associated security risks and not significant gains in most cases. What would make MySQL Multiple Queries API more usable ?

Top 5 Wishes for MySQL

About a week ago Marten send me email pointing to his article published on Jays Blog (Come on Marten, it is time for you to get your own blog). I should have replied much earlier but only found time to do that now. So here is my list 1. Be Pluggable Unlike many OpenSource projects […]

Galera replication – how to recover a PXC cluster

Galera replication for MySQL brings not only the new, great features to our ecosystem, but also introduces completely new maintenance techniques. Are you concerned about adding such new complexity to your MySQL environment? Perhaps that concern is unnecessarily. I am going to present here some simple tips that hopefully will let fresh Galera users prevent […]

Increasing slow query performance with the parallel query execution

MySQL and Scaling-up (using more powerful hardware) was always a hot topic. Originally MySQL did not scale well with multiple CPUs; there were times when InnoDB performed poorer with more  CPU cores than with less CPU cores. MySQL 5.6 can scale significantly better; however there is still 1 big limitation: 1 SQL query will eventually use only […]

Benchmarking single-row insert performance on Amazon EC2

I have been working for a customer benchmarking insert performance on Amazon EC2, and I have some interesting results that I wanted to share. I used a nice and effective tool iiBench which has been developed by Tokutek. Though the “1 billion row insert challenge” for which this tool was originally built is long over, […]

Distributed Set Processing with Shard-Query

Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: […]

Introducing our Percona Live speakers

We have mostly finalized the Percona Live schedule at this point, and I thought I’d take a few minutes to introduce who’s going to be speaking and what they’ll cover. A brief explanation first: we’ve personally recruited the speakers, which is why it has been a slow process to finalize and get abstracts on the […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]