The latest from the MySQL community

We would like to return to the regular announcements about where you can find MySQL Community team or MySQL experts at during Nov-Dec 2020. All the shows we are attending by end of this year are mostly VIRTUAL ones. Please find more details below:

• November, 2020:

  • GSCC2020/Virtual, November 14, 2020, @5:00-6:00pm

    • David Stokes, the MySQL Community Manager will be talking about "MySQL 8.0 Features for Developers"
  • MoodleMoot Global/Virtual, Nov 16-18, 2020
    • Please visit our online booth where you can talk online to our booth staff. Please also …

Editor’s Note: Because our bloggers have lots of useful tips, every now and then we update and bring forward a popular post from the past. Today’s post was originally published on May 23, 2018.

In recent weeks I’ve been focusing on Docker in order to get a much better understanding of the containerized world that is materializing in front of us. Containers aren’t just for stateless applications anymore and we’re seeing more cases where MySQL and other databases are being launched in a containerized fashion, so it’s important to know how to configure your MySQL container!

In docker hub, you will see an option for this by doing a volume mount from the Docker host to the container on /etc/mysql/conf.d. But the problem is that the container image you’re using may …

While I’m switching labs next term after more than a decade with more comprehensive lab set, I’m hoping the new exercises build the students’ core SQL skill set. Next term, I hope to see whether the change is successful. I’ve opted for using Alan Beaulieu’s Learning SQL: Generate, Manipulate, and Retrieve Data, 3rd Edition, because it’s a great book and uses the MySQL database.

One exercise that the students will lose is a data migration exercise from a badly designed common_lookup table to a well designed common_lookup table. The starting point is shown below on the left and the fixed version is on the right.

         …

In the previous blog, we saw that users don’t lose anything by moving to MySQL on ARM. Infact, users are set to gain performance and save cost. In this blog post we will see performance numbers and analyze them to understand points where ARM scores.

Benchmarking Setup

Benchmarking is done using sysbench. We have used the CPM model. You can read more about it here. In short the idea is to keep the cost the same and hunt for comparable configuration.

• Server Configuration:
  • sysbench 100 tables * 3 millions (roughly 69 GB of data)
  • We tried 2 combinations:
    • CPU Bound: buffer pool = 80 GB so complete data in memory (lesser IO).
    • IO Bound: buffer pool = 35 …

Software development is always moving forward, and the latest version is always the best ... until the next one arrives.  When you visit the MySQL Ndb Cluster downloads page, you are naturally recommended to pull the latest MySQL Cluster 8.0.22 (announcement), but sometimes it is good to look back at the journey taken to reach this point.

7.x release series

Prior to the 8.0 releases, MySQL Ndb Cluster had a sequence of 7.x (x=0..6) releases based on MySQL Server versions 5.1, 5.6, 5.7.  In each of the 7.x release series, MySQL Ndb Cluster was under feature development for some time, producing a number of minor releases, until eventually one minor release was validated as being acceptable as the first generally available (GA) …

Google Cloud SQL for MySQL is a fully-managed database service that helps you set up, maintain, manage, and administer your MySQL relational databases on Google Cloud Platform. However, there are differences between Cloud SQL and standard MySQL functionality like limited control, restricted resources, data locality, budget and security, which may influence your final decision to move out from the Google Cloud SQL instances and host the database service in the on-premises infrastructure instead.

This blog post will walk you through how to perform online migration from Google Cloud SQL to an on-premises server. Our target database on the on-premises server is a Debian server, but the steps and procedures shall apply on other versions of Linux as well as long as packages are …

For what reason should I use a real multi-Primary setup?
To be clear, not a multi-writer solution where any node can become the active writer in case of needs, as for PXC or PS-Group_replication.
No, we are talking about a multi-Primary setup where I can write at the same time on multiple nodes.
I want to insist on this “why?”.

After having excluded the possible solutions mentioned above, both covering the famous 99,995% availability, which is 26.30 minutes downtime in a year, what is left?

Disaster Recovery? Well that is something I would love to have, but to be a real DR solution we need to put several kilometers (miles for imperial) in the middle. 

And we know (see here and …

This blog discusses new features about the persisted system variables and how we can use it to make variable changes persistent. The MySQL server maintains system variables that control its operations. The dynamic variables used prior to the MySQL 8 release are not persistent and are reset upon restart. These variables can be changed at runtime using the SET statement to affect the operation of the current server instance but we have to manually update my.cnf config file to make them persistent. In many cases, updating my.cnf from the server-side is not a convenient option, and leaving the variable just updated dynamically reverts on the subsequent restart without any history.

Persisted system variables are one of the useful features introduced in MySQL 8. The new functionality helps DBAs update the variables dynamically and register them without touching the configuration files from the server-side.

How to Persist the Global …

I am always surprised to learn something new whenever I talk to a member of the open-source community. No matter how much I think I have heard of every use case there is for Liquibase (and database change management in general), I always hear something that makes this space still feel new. There’s always something left to discover.

Today, that new something is the problem of how to perform large batches of changes with SQL ALTER TABLE statements. No problem you say? Okay, but this ALTER needs to happen in production. Still not worried? Well, let’s say you have millions of rows, and because you’re so successful, you have many transactions happening per minute (maybe even per second). Yeah…now we are talking. You can’t alter the table because you can’t afford to lock that table for the …

I am always surprised to learn something new whenever I talk to a member of the open-source community. No matter how much I think I have heard of every use case there is for Liquibase (and database change management in general), I always hear something that makes this space still feel new. There’s always something left to discover.

Today, that new something is the problem of how to perform large batches of changes with SQL ALTER TABLE statements. No problem you say? Okay, but this ALTER needs to happen in production. Still not worried? Well, let’s say you have millions of rows, and because you’re so successful, you have many transactions happening per minute (maybe even per second). Yeah…now we are talking. You can’t alter the table because you can’t afford to lock that table for the …