MySQL stored procedures, functions and triggers are tempting constructs for application developers. However, as I discovered, there can be an impact on database performance when using MySQL stored routines. Not being entirely sure of what I was seeing during a customer visit, I set out to create some simple tests to measure the impact of triggers on database performance. The outcome might surprise you.

Why stored routines are not optimal performance wise: short version

Recently, I worked with a customer to profile the performance of triggers and stored routines. What I’ve learned about stored routines: “dead” code (the code in a branch which will never run) can still significantly slow down the response time of a function/procedure/trigger. We will need to be careful to clean up what we do not need.

Profiling MySQL stored functions

Let’s compare these four simple stored functions (in MySQL 5.7): …

Ever since AMD released their EPYC CPU for servers I wanted to test it, but I did not have the opportunity until recently, when Packet.net started offering bare metal servers for a reasonable price. So I started a couple of instances to test Percona Server for MySQL under this CPU. In this benchmark, I discovered some interesting discrepancies in performance between  AMD and Intel CPUs when running under systemd .

The set up

To test CPU performance, I used a read-only in-memory sysbench OLTP benchmark, as it burns CPU cycles and no IO is performed by Percona Server.

For this benchmark I used Packet.net c2.medium.x86 instances powered by AMD EPYC …

This post is mainly inspired by findings from the previous testing of MySQL 8.0 on TPCC workload(s) and observations from IO-bound Sysbench OLTP on Optane -vs- SSD. But also by several "urban myths" I'm often hearing when discussing with users about their IO-bound OLTP performance problems :
Myth #1 : "if I'll double the number of my storage drives -- I'll get x2 times better TPS !"

• this was mostly true during "HDD era", and again..
• (ex.: a single thread app doing single random IO reads from a single HDD will not go faster by doing the same from 2x HDD -- similar like single thread workload will not run faster on 8CPU cores -vs- 2CPU cores, etc.)
• all depends …

MySQL Performance on IO-bound workloads is still extremely depending on the underlaying storage layer (thus is directly depending on your Storage Performance).. Indeed, flash storage is definitively changing the game, but even with flash there is, as usual, "flash and flash" -- all storage vendors are improving their stuff constantly, so every time you have something new to discover and to learn ;-)) During all my MySQL 8.0 GA tests I was very pleasantly surprised by IO performance delivered by Intel Optane SSD. However, what the storage device can deliver alone on pure IO tests is not at all the same to what you could observe when it's used by MySQL -- unfortunately, in the past I've observed many cases when with a device claimed to be x2 times faster we were even not observing 10% gain.. But MySQL 8.0 is probably the most best placed MySQL version today to re-visit all this IO-bound story (there are many "under-hood" changes in the code helping to …

Generally, when I'm analyzing MySQL Performance on Linux with "localhost" test workloads, I'm configuring client connections to use IP port (loopback) to connect to MySQL Server (and not UNIX socket) -- this is still at least involving IP stack in the game, and if something is going odd on IP, we can be aware ahead about. And indeed, it already helped several times to discover such kind of problems even without network links between client/server (like this one, etc.). However, in the past we also observed a pretty significant difference in QPS results when IP port was used comparing to UNIX socket (communications via UNIX socket were going near 15% faster).. Over a time with newer OL kernel releases this gap became smaller and smaller. But in all such …

If you attended my latest Troubleshooting MySQL Concurrency Issues with Load Testing Tools webinar you learned how I exploit benchmarking tools to replicate locking issues and crashes. But I told you nothing about proper use of these tools: for reliable benchmarks. I did not tell you that for a reason… I am just a Support Engineer and not a benchmarking expert.

And I have a dream. I want to invite world famous MySQL benchmarking experts for a Percona webinar and ask them for their secrets. I have a pretty long list of my own questions, but in order to make 1-hour webinar productive, we need to concentrate on just a few of the hottest ones. Therefore I need your help.

Please add your questions into the comments field of this blog post. Then we will choose the most important and/or most popular of …

In this blog, I will provide answers to the Q & A for the Troubleshooting MySQL Concurrency Issues with Load Testing Tools webinar.

First, I want to thank everybody for attending my May 23, 2018, webinar on troubleshooting tools for MySQL. The recording and slides for the webinar are available here. Below is the list of your questions that I was unable to answer fully during the webinar.

Q: What do you recommend for benchmarking NDB cluster? Which should be used and how?

A: The issue with benchmarking NDB cluster is not the tool choice, …

Generally TPC-C benchmark workload is considered as one of the #1 references for Database OLTP Performance. On the same time, for MySQL users it's often not something which is seen as "the most compelling" for performance evaluations.. -- well, when you're still fighting to scale with your own very simple queries, any good result on something more complex may only look as "fake" ;-)) So, since a long time Sysbench workloads remained (and will remain) as the main #1 "entry ticket" for MySQL evaluation -- the most simple to install, to use, and to point on some sensible issues (if any). Specially that since new Sysbench version 1.0 a lot of improvements were made in Sysbench code itself, it really scales now, has the lowest ever overhead, and also allowing you to add your own test scenario via extended LUA scripts (and again, with lowest ever overhead) -- so, anyone can easily add …

As part of my benchmarks of binary logs, I’ve decided to check how the recently released MySQL 8.0 performance is affected in similar scenarios, especially as binary logs are enabled by default. It is also interesting to check how MySQL 8.0 performs against the claimed performance improvements in redo logs subsystem.

I will use a similar setup as in my last blog with MySQL 8.0, using the utf8mb4 charset.

I have a few words about MySQL 8.0 tuning. Dimitri’s recommends in his blog posts using innodb_undo_log_truncate=off and …

I want to take a closer look at MySQL performance with binary logs enabled on different filesystems, especially as MySQL 8.0 comes with binary logs enabled by default.

As part of my benchmarks of the MyRocks storage engine, I’ve noticed an unusual variance in throughput for the InnoDB storage engine, even though we spent a lot of time making it as stable as possible in Percona Server for MySQL. In the end, the culprit was enabled binary logs. There is also always the question, “If there is a problem with EXT4, does XFS perform differently?” To answer that, I will repeat the same benchmark on the EXT4 and XFS filesystems.

You can find our previous experiments with binary logs here: …