Demonstrating distributed set processing performance Shard-Query + ICE scales very well up to at least 20 nodes This post is a detailed performance analysis of what I’ve coined “distributed set processing”. Please also read this post’s “sister post” which describes the distributed set processing technique. Also, remember that Percona can help you get up and […]
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.Â 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:
I wrote couple of weeks ago on dangers of bad cache design. Today I’ve been troubleshooting the production down case which had fair amount of issues related to how cache was used. The deal was as following. The update to the codebase was performed and it caused performance issues, so it was rolled back but […]
I worked on the problem recently which showed itself as rather low MySQL load (probably 5% CPU usage and close to zero IO) would spike to have hundreds instances of threads running at the same time, causing intense utilization spike and server very unresponsive for anywhere from half a minute to ten minutes until everything […]
This is part two in my six part series on business intelligence, with a focus on OLAP analysis. Part 1 – Intro to OLAP Identifying the differences between a data warehouse and a data mart. (this post) Introduction to MDX and the kind of SQL which a ROLAP tool must generate to answer those queries. […]
When we’re looking at mk-query-digest report we typically look at the Queries causing the most impact (sum of the query execution times) as well as queries having some longest samples. Why are we looking at these ? Queries with highest Impact are important because looking at these queries and optimizing them typically helps to improve […]
First time I heard about Galera on Percona Performance Conference 2009, Seppo Jaakola was presenting “Galera: Multi-Master Synchronous MySQL Replication Clusters”. It was impressed as I personally always wanted it for InnoDB, but we had it in plans at the bottom of the list, as this is very hard to implement properly. The idea by […]
Resolving extreme database overload for the customer recently I have found about 80 copies of same cron job running hammering the database. This number is rather extreme typically the affect is noticed and fixed well before that but the problem with run away cron jobs is way to frequent. If slow down happens on the […]
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:
Note: This blog post is part 1 of 4 on building our training workshop.
The Percona training workshop will not cover sharding. If you follow our blog, you’ll notice we don’t talk much about the subject; in some cases it makes sense, but in many we’ve seen that it causes architectures to be prematurely complicated.
So let me state it: You don’t want to shard.
Optimize everything else first, and then if performance still isn’t good enough, it’s time to take a very bitter medicine. The reason you need to shard basically comes down to one of these two reasons