Over the last few years, Domas’s technique of using GDB as a profiler has become a key tool in helping us analyze MySQL when customers are having trouble. We have our own implementation of it in Percona Toolkit (pt-pmp) and we gather GDB backtraces from pt-stalk and pt-collect. Although it’s helped us figure out a […]
Search Results for: mysql big memory
It is no secret that bugs related to multithreading–deadlocks, data races, starvations etc–have a big impact on application’s stability and are at the same time hard to find due to their nondeterministic nature. Any tool that makes finding such bugs easier, preferably before anybody is aware of their existence, is very welcome.
When we’re looking at benchmarks we typically run some stable workload and we run it in isolation – nothing else is happening on the system. This is not however how things happen in real world when we have significant variance in the load and many things can be happening concurrently. It is very typical to […]
As part of work on “High Performance MySQL, 3rd edition”, Baron asked me to compare different MySQL version in some simple benchmark, but on decent hardware. So why not.
It is known that MySQL due internal limitations is not able to utilize all CPU and IO resources available on modern hardware. Idea is to run multiple instances of MySQL to gain better performance on Fusion-io ioDrive card. Full report is available in PDF
We raised topic of problems with flushing in InnoDB several times, some links: InnoDB Flushing theory and solutions MySQL 5.5.8 in search of stability This was not often recurring problem so far, however in my recent experiments, I observe it in very simple sysbench workload on hardware which can be considered as typical nowadays.
A while ago I started a series of posts showing benchmark results on Amazon EC2 servers with RAID’ed EBS volumes and MySQL, versus RDS machines. For reasons that won’t add anything to this discussion, I got sidetracked, and then time passed, and I no longer think it’s a good idea to publish those blog posts […]
“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding […]
You may have seen in the last couple of weekly news posts that Baron mentioned we are working on a new adaptive flushing algorithm in InnoDB. In fact, we already have three such algorithms in Percona Server (reflex, estimate, keep_average). Why do we need one more? Okay, first let me start by showing the current […]
Amazon’s Relational Database Service (RDS) is a cloud-hosted MySQL solution. I’ve had some clients hitting performance limitations on standard EC2 servers with EBS volumes (see SSD versus EBS death match), and one of them wanted to evaluate RDS as a replacement. It is built on the same technologies, but the hardware and networking are supposed […]