Way back in 2010, MySQL Bug 57241 was filed, pointing out that the “swap insanity” problem was getting serious on x86 systems – with NUMA being more and more common back then.

The swapping problem is due to running out of memory on a NUMA node and having to swap things to other nodes (see Jeremy Cole‘s blog entry also from 2010 on the topic of swap insanity). This was back when 64GB and dual quad core CPUs was big – in the past five years big systems have gotten bigger.

Back then there were two things you could do to have your system be usable: 1) numa=off as kernel boot parameter (this likely has other implications though) and 2) “numactl –interleave all” in mysqld_safe …

Yesterday, I got the basics going for MySQL Cluster on POWER. Today, I finished up a couple more patches to improve performance and ran some benchmarks.

This is on a 3.7Ghz POWER8 machine with non-balanced memory (only 2 of the 4 NUMA nodes have memory, so we have less total memory bandwidth than we could have, plus I’m going to bind ndbmtd to the CPUs in these NUMA nodes)

With a setup of a single replica and two data nodes on the one machine (each bound to a specific NUMA node), running the flexAsync benchmark on MySQL Cluster 7.3.7, I could get around:

• 3.2 million reads/sec
• 2.6 million deletes/sec
• 2.4 million updates/sec
• 2.4 million inserts/sec.

So, that’s at least in the right ballpark for a first go.

(I’m running this on a big endian host …

I saw a post on profiling memory usage today and this reminds me of several discussions I have had with different people.

Why would you want to profile the memory usage? Usually to see where memory is allocated and for what purposes, and usually you only care when memory usage is higher than expected. That is a DBA normally wants to use all available memory on a server for mysqld, whatever that size may be.

Configuration parameters may be inappropriate and need adjusting, so having a way to determine the range of memory usage based on those parameters would be most helpful.  However, the configuration parameters as a whole put no limit on memory used, so different workloads can quite easily lead to memory being insufficient on the OS, triggering swapping or perhaps the …