While the PMM team works hard on our PMM 2.0 release, we have been working on a few things in the background which we’d like to show off !  In particular we have developed a new dashboard that displays metrics related to memory usage on Linux systems. The dashboard leverages information collected by node_exporter. The graphs take advantage of  /proc filesystem files, specifically:

• meminfo: Provides information about distribution and utilization of memory. This varies by architecture and compile options.
• vmstat: Provides information about block IO and CPU activity in addition to memory.

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In this post we will review the most important Linux settings to adjust for performance tuning and optimization of a MySQL database server. We’ll note how some of the Linux parameter settings used OS tuning may vary according to different system types: physical, virtual or cloud. Other posts have addressed MySQL parameters, like Alexander’s blog MySQL 5.7 Performance Tuning Immediately After Installation. That post remains highly relevant for the latest versions of MySQL, 5.7 and 8.0. Here we will focus more on the Linux operating system parameters that can affect database performance.

Server and Operating System

Here are some Linux parameters that you should check and consider modifying if you need to improve database performance.

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Troubleshooting crashes is never a fun task, especially if MySQL does not report the cause of the crash. For example, when MySQL runs out of memory. Peter Zaitsev wrote a blog post in 2012: Troubleshooting MySQL Memory Usage with a lots of useful tips. With the new versions of MySQL (5.7+) and performance_schema we have the ability to troubleshoot MySQL memory allocation much more easily.

In this blog post I will show you how to use it.

First of all, there are 3 major cases when MySQL will crash due to running out of memory:

1. MySQL tries to allocate more memory than available because we specifically told it to do so. For example: you did not set innodb_buffer_pool_size correctly. This is very easy to fix
2. There is some other process(es) on the server that allocates RAM. It can be the application …

Since MySQL 5.7.5, we have been able to resize dynamically the InnoDB Buffer Pool. This new feature also introduced a new variable — innodb_buffer_pool_chunk_size — which defines the chunk size by which the buffer pool is enlarged or reduced. This variable is not dynamic and if it is incorrectly configured, could lead to undesired situations.

Let’s see first how innodb_buffer_pool_size , innodb_buffer_pool_instances  and innodb_buffer_pool_chunk_size interact:

The buffer pool can hold several instances and each instance is divided into chunks. There is some information that we need to take into account: the number of instances can go from 1 to 64 and the total amount of chunks should not exceed 1000.

So, for a server with 3GB RAM, a buffer pool of 2GB with 8 instances and chunks at default value (128MB) we are going to get 2 chunks per instance:

This means that there will be 16 chunks.

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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 …

My colleague Mike Hamrick, who I'm very fortunate to work with, made a presentation on some cool things you can do with top: http://tinyurl.com/48pmu83. These are some great tips that every MySQL DBA or developer should watch!