Over the last year, I have been pursuing a part time hobby project exploring ways to squeeze as much data as possible in MySQL. As you will see, there are quite a few different ways. Of course things like compression ratio matters a lot but, other items like performance of inserts, selects and updates, along with the total amount of bytes written are also important. When you start combining all the possibilities, you end up with a large set of compression options and, of course, I am surely missing a ton. This project has been a great learning opportunity and I hope you’ll enjoy reading about my results. Given the volume of results, I’ll have to write a series of posts. This post is the first of the series. I also have to mention that some of my work overlaps work done by one of my colleague, Yura Sorokin, in a …

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): …

In MySQL 8.0 there are two new features designed to support lock handling: NOWAIT and SKIP LOCKED. In this post, we’ll look at how MySQL 8.0 handles hot rows. Up until now, how have you handled locks that are part of an active transaction or are hot rows? It’s likely that you have the application attempt to access the data, and if there is a lock on the requested rows, you incur a timeout and have to retry the transaction. These two new features help you to implement sophisticated lock handling scenarios allowing you to handle timeouts better and improve the application’s performance.

To demonstrate I’ll use this product table.

mysql> select @@version;
+-----------+
| @@version |
+-----------+
| 8.0.11    |
+-----------+
1 row in set (0.00 sec)

CREATE TABLE `product` (
`p_id` int(11) NOT NULL AUTO_INCREMENT,
`p_name` varchar(255) DEFAULT NULL,
`p_cost` decimal(19,4) NOT NULL,
`p_availability` enum('YES','NO') …

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 …

Too often developers and DBAs struggle to pinpoint the root cause of MySQL database performance issues, and then spend too much time in trying to fix them. Wouldn’t it be great to bypass wasted guesswork and get right to the issue?

In our upcoming webinar Tired of MySQL Making You Wait? we’re going to help you discover how to significantly increase the performance of your applications and reduce database response time.

In this webinar, Principal Architect Alexander Rubin and Database Evangelist Janis Griffin will provide the key steps needed to identify, prioritize, and improve query performance.

They will discuss the following topics:

• Wait time analytics using …

Application issues, downtimes and outages are the responsibility of IT to resolve. However, at the end of the day they are, essentially, business issues.
 
Businesses compete for customers online everyday and the latter are not a patient bunch. Every second of your web application performance counts building up or taking away both revenue and brand reputation. There’s always a risk that even though your application may appear to be working fine, its flow’s key parts, such as shopping carts, registration pages, etc. may not be functioning properly. So it’s critical to have a full controll across the entire application delivery chain. With Node.js, MySQL, Oracle, Java/JMX, Log, and Tomcat application monitors, you can track your app’s performance bottom-up.
 
Check out the infographic below to see …

Jet Profiler is a great MySQL  profiler. As the world of operating systems is getting more and more mixed, Jet Profiler offers a huge advantage: It is a Java based application and therefore able to run on Windows, Max OS X as well as on Linux.

Most of the time Java based applications tend to be very slow, however Jet Profiler shows that Java based applications can be fast and responsive as well. Even after hours of recording the UI stays responsive. To give you a working example, I had it recording on a server and real world load.

A nice feature of Jet Profiler is the setting for the polling interval. If you have a very, very busy server the polls could interfere with …

Maximize your strengths, minimize your weaknesses.

You can apply this approach to many things in life, I apply it to describing and using MySQL the product, and it’s components. The Query Cache like many features in MySQL, and indeed features in many different RDBMS products (don’t get me started on Oracle *features*) have relative benefits. In one context it can be seen as ineffective, or even detrimental to your performance, however it’s course grain nature makes it both trivial to disable dynamically (SET GLOBAL query_cache_size=0;), and also easy to get basic statistics on current performance (SHOW GLOBAL STATUS LIKE ‘QCache%’;) to determine effectiveness and action appropriately.

The Query Cache is course grained, that is it is rather simple/dumb in nature. When you understand the path of execution of a query within the MySQL kernel you learn a few key things.

• When enabled, by default the Query …