Sysbench has three distribution for random numbers: uniform, special and gaussian. I mostly use uniform and special, and I feel that both do not fully reflect my needs when I run benchmarks. Uniform is stupidly simple: for a table with 1 mln rows, each row gets equal amount of hits. This barely reflects real system, it also does not allow effectively test caching solution, each row can be equally put into cache or removed.
I’ve previously provided an example of using MySQL Cluster Manager to add nodes to a running MySQL Cluster deployment but I’ve since received a number of questions arou
You might have heard that Oracle made the decision not to support MySQL for IBM i any longer. This is certainly understandable. However, there are still users who want to continue running IBM i and MySQL.
In my previous post with results for Fusion-io ioDrive we saw some instability in results, I was pointed that it may be fixed in new drivers VSL 3.1.1. I am not sure if this driver is available for everyone – if you are interested, please contact your Fusion-io support representative. I installed new drivers and firmware, and in fact, the result improved.
One of the very frequent cases with performance problems with MySQL is what they happen every so often or certain times. Investigating them we find out what the cause is some batch jobs, reports and other non response time critical activities are overloading the system causing user experience to degrade.
The tools we’ve redesigned in Percona Toolkit recently have moved away from a legacy technique for operating on small numbers of rows at a time, towards a more reliable and predictable method. We call the old version “chunking” and the new version “nibbling.” Many other MySQL tools I’ve seen either operate on entire tables, or use the “chunking” technique and are exposed to the problems it creates. I’ll compare the two briefly to explain the differences.