I often need to install a certain version of MySQL, MariaDB, or Percona Server for MySQL to run some experiments, whether to check for behavior differences or to provide tested instructions. In this blog series, I will look into how you can install MySQL, MariaDB, or Percona Server for MySQL with Docker.  This post, part one, is focused on MySQL Server.

Docker is actually not my most preferred way as it does not match a typical production install, and if you look at service control behavior or file layout it is quite different.  What is great about Docker though is that it allows installing the latest MySQL version – as well as any other version – very easily.

Docker also is easy to use when you need a simple, single instance.  If you’re looking into some replication-related behaviors, …

In a previous post, I explained how you can take advantage of Oracle’s “Always Free” Cloud instance to obtain a free Oracle Cloud compute instance (virtual machine) and install a copy of MySQL – without having to pay a setup fee and without incurring any monthly charges. And, you can have two free compute instances per account.

This free Cloud option from Oracle is great. I can think of a lot of ways to utilize a free Oracle Cloud compute instance – but the first one that came to …

In the previous blog we showed you how to set up an environment in Amazon AWS EC2 that consists of a Percona Server 8.0 Replication Cluster (in Master - Slave topology). We deployed ProxySQL and we configured our application (Sysbench). 

We also used ClusterControl to make the deployment easier, faster and more stable. This is the environment we ended up with...

This is how it looks in ClusterControl:

In this blog post we are going to review the requirements and show you how, in this setup, you can seamlessly perform master switches.

Seamless Master Switch with ProxySQL …

In this post, we will explore one approach to MySQL high availability with ProxySQL, Consul and Orchestrator.

This is a follow up to my previous post about a similar architecture but using HAProxy instead. I’ve re-used some of the content from that post so that you don’t have to go read through that one, and have everything you need in here.

Let’s briefly go over each piece of the puzzle:

– ProxySQL is in charge of connecting the application to the appropriate backend (reader or writer).

It can be installed on each application server directly or we can have an intermediate connection layer with one or more ProxySQL servers. The former probably makes sense if you have a small number of application servers; as the number grows, the latter option becomes more attractive. Another scenario for the …

MySQL Cluster 8.0.18 RC2 was released a few weeks back packed with a set of
new interesting things.

One major change we have done is to increase the number of data nodes from 48 to
144. There is also ongoing work to fully support 3 and 4 replicas in MySQL
Cluster 8.0. NDB has actually always been designed to handle up to 4 replicas.
But the test focus have previously been completely focused on 2 replicas. Now we
expanded our test focus to also verify that 3 and 4 replicas work well. This means
that with NDB 8.0 we will be able to confidently support 3 and 4 replicas.
This means that with NDB 8.0 it will be possible to have 48 node
groups with 3 replicas in each node group in one cluster.

The higher number of nodes in a cluster gives the possibility to store even more
data in the cluster. So with 48 node groups it is possible to store 48 TByte of
…

To illustrate how easy it’s to see who’s trying to access data they have not been granted for, we will first create a schema with two tables:

mysql> create database mydata;
mysql> use mydata
mysql> create table table1 (id int auto_increment primary key, 
              name varchar(20), something varchar(20));
mysql> create table table2 (id int auto_increment primary key, 
              name varchar(20), something varchar(20));

Now, let’s create a user :

mysql> create user myuser identified by 'mypassword';

And as it’s always good to talk about SQL ROLES, let’s define 3 roles for our user:

• myrole1: user has access to both tables in their entirety, reads and writes
• myrole2: user has access only to `table2`, reads and writes
• myrole3: user has only access to the column `name`of `table1` and …

MySQL InnoDB Cluster consists of 3 components:

• MySQL Group Replication (a group of database server which replicates to each other with fault tolerance).
• MySQL Router (query router to the healthy database nodes)
• MySQL Shell (helper, client, configuration tool)

In the first part of this walkthrough, we are going to deploy a MySQL InnoDB Cluster. There are a number of hands-on tutorial available online but this walkthrough covers all the necessary steps/commands to install and run the cluster in one place. We will be covering monitoring, management and scaling operations as well as some gotchas when dealing with MySQL InnoDB Cluster in the second part of this blog post.

The following diagram illustrates our post-deployment architecture:

We are going to deploy a total of 4 nodes; A three-node MySQL Group Replication and one MySQL router node co-located within the application …

In my previous blog, I have explained how the MySQL clone plugin works internally. In this blog, I am going to do a comparison of  Backup and Recovery speed of MySQL clone plugin with other available mysql open source backup tools.

Below tools are used for speed comparison of Backup and Recovery,

1. Clone-Plugin
2. Xtrabackup
3. mysqldump
4. mydumper with myloader
5. mysqlpump

Test …

For a long time, the only algorithm for executing a join in MySQL has been variations of the nested loop algorithm. With the release of MySQL 8.0.18, the server can now execute joins using hash join. This blog post will have a look at how it works, when it is used, and how it compares to the old join algorithms in MySQL in terms of performance.…

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Recently, at Percona Live Europe 2019, Dimitri Kravchuk from Oracle mentioned that he observed some unclear drop in performance for MySQL on an ext4 filesystem with the latest Linux kernels. I decided to check this case out on my side and found out that indeed, starting from linux kernel 4.9, there are some cases with notable (up to 2x) performance drops for ext4 filesystem in direct i/o mode.

So what’s wrong with ext4? It started in 2016 from the patch that was pushed to kernel 4.9: “ext4: Allow parallel DIO reads”. The purpose of that patch was to help to improve read scalability in direct i/o mode. However, along with improvements in pure read workloads, it also introduced regression in intense mixed random read/write scenarios. And it’s quite weird, but this issue had not been …