November 23, 2014

Profiling MySQL Memory Usage With Valgrind Massif

There are times where you need to know exactly how much memory the mysqld server (or any other program) is using, where (i.e. for what function) it was allocated, how it got there (a backtrace, please!), and at what point in time the allocation happened. For example; you may have noticed a sharp memory increase […]

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 […]

Predicting Performance improvements from memory increase

One common question I guess is how much should I see performance improved in case I increase memory say from 16GB to 32GB. The benefit indeed can be very application dependent – if you have working set of say 30GB with uniform data access raising memory from 16GB to 32GB can improve performance order of […]

MySQL Server Memory Usage

Every so often people ask me the question how should they estimate memory consumption by MySQL Server in given configuration. What is the formula they could use. The reasons to worry about memory usage are quite understandable. If you configure MySQL Server so it uses too small amount of memory it will likey perform suboptimally. […]

Prevent MySQL downtime: Set max_user_connections

One of the common causes of downtime with MySQL is running out of connections. Have you ever seen this error? “ERROR 1040 (00000): Too many connections.” If you’re working with MySQL long enough you surely have. This is quite a nasty error as it might cause complete downtime… transient errors with successful transactions mixed with […]

Reference architecture for a write-intensive MySQL deployment

We designed Percona Cloud Tools (both hardware and software setup) to handle a very high-intensive MySQL write workload. For example, we already observe inserts of 1bln+ datapoints per day. So I wanted to share what kind of hardware we use to achieve this result. Let me describe what we use, and later I will explain […]

Do not trust vmstat IOwait numbers

I’ve been running a benchmark today on my old test box with conventional hard drives (no raid with BBU) and noticed something unusual in the CPU utilization statistics being reported. The benchmark was run like this:

Which means: create 64 threads and hammer the database with queries as quickly as possible. As the test […]

Tips on benchmarking Go + MySQL

We just released, as an open source release, our new percona-agent (https://github.com/percona/percona-agent), the agent to work with Percona Cloud Tools. This agent is written in Go. I will give a webinar titled “Monitoring All MySQL Metrics with Percona Cloud Tools” on June 25 that will cover the new features in percona-agent and Percona Cloud Tools, […]

ScaleArc: Benchmarking with sysbench

ScaleArc recently hired Percona to perform various tests on its database traffic management product. This post is the outcome of the benchmarks carried out by Uday Sawant (ScaleArc) and myself. You can also download the report directly as a PDF here. The goal of these benchmarks is to identify the potential overhead of the ScaleArc […]