April 18, 2014

Percona XtraDB Cluster: Failure Scenarios with only 2 nodes

During the design period of a new cluster, it is always advised to have at least 3 nodes (this is the case with PXC but it’s also the same with PRM). But why and what are the risks ? The goal of having more than 2 nodes, in fact an odd number is recommended in […]

Impact of memory allocators on MySQL performance

MySQL server intensively uses dynamic memory allocation so a good choice of memory allocator is quite important for the proper utilization of CPU/RAM resources. Efficient memory allocator should help to improve scalability, increase throughput and keep memory footprint under the control. In this post I’m going to check impact of several memory allocators on the […]

Troubleshooting MySQL Memory Usage

One of the most painful troubleshooting tasks with MySQL is troubleshooting memory usage. The problem usually starts like this – you have configured MySQL to use reasonable global buffers, such as innodb_buffer_size, key_buffer_size etc, you have reasonable amount of connections but yet MySQL takes much more memory than you would expect, causing swapping or other […]

Benchmarking Galera replication overhead

When I mention Galera replication as in my previous post on this topic, the most popular question is how does it affect performance. Of course you may expect performance overhead, as in case with Galera replication we add some network roundtrip and certification process. How big is it ? In this post I am trying […]

Aligning IO on a hard disk RAID – the Benchmarks

In the first part of this article I have showed how I align IO, now I want to share results of the benchmark that I have been running to see how much benefit can we get from a proper IO alignment on a 4-disk RAID1+0 with 64k stripe element. I haven’t been running any benchmarks […]

Aligning IO on a hard disk RAID – the Theory

Now that flash storage is becoming more popular, IO alignment question keeps popping up more often than it used to when all we had were rotating hard disk drives. I think the reason is very simple – when systems only had one bearing hard disk drive (HDD) as in RAID1 or one disk drive at […]

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 […]

Impact of the number of idle connections in MySQL

Be careful with my findings, I appear to have compile in debug mode, I am redoing the benchmarks. Updated version here. I recently had to work with many customers having large number of connections opened in MySQL and although I told them this was not optimal, I had no solid arguments to present. More than […]

MySQL-Memcached or NOSQL Tokyo Tyrant – part 3

This is part 3 of our series.  In part 1 we talked about boosting performance with memcached on top of MySQL, in Part 2 we talked about running 100% outside the data with memcached, and now in Part 3 we are going to look at a possible solution to free you from the database.  The […]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see http://www.mysqlperformanceblog.com/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron’s example I also run the same load against MonetDB. Reading comments to Baron’s post I tied to load the same data to LucidDB, but I was not successful in this. I tried to analyze a bigger dataset and I took public […]