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 [...]
InnoDB compression woes
InnoDB compression is getting some traction, and I see quite contradictory opinions. Someone has successful deployments in productions, and someone says that compression in current implementation is useless. To get some initial impression about performance I decided to run some sysbench with multi-tables benchmarks. I actually was preparing to do complex research, but even first [...]
Using any general purpose computer as a special purpose SIMD computer
Often times, from a computing perspective, one must run a function on a large amount of input. Often times, the same function must be run on many pieces of input, and this is a very expensive process unless the work can be done in parallel. Shard-Query introduces set based processing, which on the surface appears [...]
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: [...]
Intel Nehalem vs AMD Opteron shootout in sysbench workload
Having two big boxes in our lab, one based Intel Nehalem (Cisco UCS C250) and second on AMD Opteron (Dell PowerEdge R815), I decided to run some simple sysbench benchmark to compare how both CPUs perform and what kind of scalability we can expect.
Modeling MySQL Capacity by Measuring Resource Consumptions
There are many angles you can look at the system to predict in performance, the model baron has published for example is good for measuring scalability of the system as concurrency growths. In many cases however we’re facing a need to answer a question how much load a given system can handle when load is [...]
Performance problem with Innodb and DROP TABLE
I’ve been working with an application which does a lot of CREATE and DROP table for Innodb tables and we’ve discovered DROP TABLE can take a lot of time and when it happens a lot of other threads stall in “Opening Tables” State. Also contrary to my initial suspect benchmarking create/drop table was CPU bound [...]
High Rate insertion with MySQL and Innodb
I again work with the system which needs high insertion rate for data which generally fits in memory. Last time I worked with similar system it used MyISAM and the system was built using multiple tables. Using multiple key caches was the good solution at that time and we could get over 200K of inserts/sec. [...]
MySQL Partitioning – can save you or kill you
I wanted for a while to write about using MySQL Partitioning for Performance Optimization and I just got a relevant customer case to illustrate it. First you need to understand how partitions work internally. Partitions are on the low level are separate table. This means when you’re doing lookup by partitioned key you will look [...]
Shard-Query adds parallelism to queries
Preamble: On performance, workload and scalability: MySQL has always been focused on OLTP workloads. In fact, both Percona Server and MySQL 5.5.7rc have numerous performance improvements which benefit workloads that have high concurrency. Typical OLTP workloads feature numerous clients (perhaps hundreds or thousands) each reading and writing small chunks of data. The recent improvements to [...]

