MySQL 8.0.22 was released roughly a week ago. It includes some nice additions to replication that we would like to call out. Here they are:

• Automatic Asynchronous Replication Connection Failover (WL#12649). This work, by Hemant Dangi, implements a mechanism in asynchronous replication that makes the replica automatically try to re-establish an asynchronous replication connection to another replication source, in case the current connection gets interrupted;
• New terminology for replica related statements (WL#14171).

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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) …

MySQL on ARM is gaining consistent momentum and community is excited about it. Beyond performance, users also tend to explore other aspects like feature-set, ecosystem, support, etc… Let’s explore what users would gain/lose by moving to mysql on arm.

Evaluation aspects

There are 4 main aspect user tend to consider while migrating database/database environment/database-setup

• Feature Set
• Performance
• Ecosystem
• Community Support

Let’s analyze MySQL on ARM from these perspectives

Feature Set

MySQL on ARM supports all the features that MySQL has to offer. We are not aware of any feature that doesn’t work or has been marked as beta on ARM. This means you don’t lose on the feature front if you decide to run mysql on arm. Beyond the mainline feature binlog-replication, group-replication, in-build plugins, authentication/security plugins all …

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 …

In a perfect world, we expect all software to run flawlessly and never have problems such as bugs and crashes. We also know that this perfect world doesn’t exist and we better be as prepared as possible to troubleshoot those types of situations. Historically, generating core dumps has been a task delegated to the kernel. If you are curious about how to enable it via Linux kernel, you can check out Getting MySQL Core file on Linux. There are a few drawbacks that pose either a limitation or a huge strain to get it working, such as:

• System-wide configuration required. This is not something DBA always has access to.
• Inability or very difficult to enable it for a specific binary only. Standards ways enable it for every software running on the box.
• Nowadays, with cloud and containers, this task has become even …

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 …

Many times, we do not want duplicate rows or values in our SQL tables. On the other hand, in some situations, it does not matter if there are duplicates present. For whatever reason, suppose duplicates have found their way into one of your tables. How can you find them quickly and easily? The ROW_NUMBER() Window function is a fantastic tool to use. Continue reading and see example queries you can apply to your own tables and find those duplicates…

Photo by Joe Green on Unsplash

OS and DB used:

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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 …

 In the previous post I showed some improvements based on using

Windows functions in rewritten TPC-H queries. In this blog post

I will discuss the improvements made in Q15 using a CTE (Common

Table Expression). This is again based on inspiration from new and

old blogs written by Öystein Grövlen (should be norwegian ö's).

Here is Q15 in TPC-H:

create view revenue (supplier_no, total_revenue) as

        select

                l_suppkey,

                sum(l_extendedprice * (1 - l_discount))

        from

                lineitem

        where

                l_shipdate >= '1996-01-01' …

If you often deploy services in the cloud, you certainly, at least once, forgot to stop a test instance. I am like you and I forgot my share of these. Another mistake I do once in a while is to provision a bigger instance than needed, just in case, and forget to downsize it. While this is true for compute instances, it is especially true for database instances. Over time, this situation ends up adding a cost premium. In this post, we’ll discuss a solution to mitigate these extra costs, the use of the RDS Aurora Serverless service.

What is Amazon Aurora Serverless?

Since last spring, Amazon unveiled a new database related product: RDS Aurora Serverless. The aim of this new product is to simplify the management around Aurora clusters. It brings a likely benefit for the end users, better control over cost. Here are some …