Why another article on this Marco?

Deadlocks is a topic covered many times and with a lot of articles on the web, also from Percona.
I suggest you review the reference section for articles on how to identify Deadlocks and from where they are generated.
So why another article?
The answer is that messages like the following are still very common:

User (John): “Marco our MySQL is having problems”
Marco: “Ok John what problems. Can you be a bit more specific?”
John: “Our log scraper is collecting that MySQL has a lot of errors”
Marco: “Ok can you share the MySQL log so I can review it?”
John: “Errors are in the application log, will share one application log”

Marco reviews the log and in it he founds:

“ERROR 1213 (40001): Deadlock found when trying to get lock;
try restarting transaction”

Marco reaction is: "Oh my ..." 

…

Why another article on this Marco?

Deadlocks is a topic covered many times and with a lot of articles on the web, also from Percona.
I suggest you review the reference section for articles on how to identify Deadlocks and from where they are generated.
So why another article?
The answer is that messages like the following are still very common:

User (John): “Marco our MySQL is having problems”
Marco: “Ok John what problems. Can you be a bit more specific?”
John: “Our log scraper is collecting that MySQL has a lot of errors”
Marco: “Ok can you share the MySQL log so I can review it?”
John: “Errors are in the application log, will share one application log”

Marco reviews the log and in it he founds:

“ERROR 1213 (40001): Deadlock found when trying to get lock;
try restarting transaction”

Marco reaction is: "Oh my ..." 

…

Yves Trudeau and Francisco Bordenave, MySQL experts at Percona, recently published a three-part post: (1) Give Love to Your SSDs – Reduce innodb_io_capacity_max!; (2) InnoDB Flushing in Action for Percona Server for MySQL; (3) Tuning MySQL/InnoDB Flushing for a Write-Intensive Workload. It’s a fantastic read from start to finish, and it made me realize: dirty pages sound bad, but they are good. I suspect the opposite (“dirty pages are not good”) is a misconception due to an incomplete picture. Let’s complete the picture.

Yves Trudeau and Francisco Bordenave, MySQL experts at Percona, recently published a three-part post: (1) Give Love to Your SSDs – Reduce innodb_io_capacity_max!; (2) InnoDB Flushing in Action for Percona Server for MySQL; (3) Tuning MySQL/InnoDB Flushing for a Write-Intensive Workload. It’s a fantastic read from start to finish, and it made me realize: dirty pages sound bad, but they are good. I suspect the opposite (“dirty pages are not good”) is a misconception due to an incomplete picture. Let’s complete the picture.

Back to part 1

Now that we had seen how to setup our environment with PXC8 is time to see how our setup will behave and what can be done in case of issues.

We will now analyse the following common situations:
- Put a node in maintenance or remove a node and insert it back
- node crash
- network failure
- proxysql node crash

The following tests are done using a java application connecting using straight JDBC connection and no connection pooling. I choose to use that more than a …

Back to part 1

Now that we had seen how to setup our environment with PXC8 is time to see how our setup will behave and what can be done in case of issues.

We will now analyse the following common situations:
- Put a node in maintenance or remove a node and insert it back
- node crash
- network failure
- proxysql node crash

The following tests are done using a java application connecting using straight JDBC connection and no connection pooling. I choose to use that more than a …

In real life, there are frequent cases where getting a running application to work correctly is strongly dependent on consistent write/read operations. This is no issue when using a single data node as a provider, but it becomes more concerning and challenging when adding additional nodes for high availability and/or read scaling.

In the MySQL dimension, I have already described it here in my blog Dirty Reads in High Availability Solution.

We go from the most loosely-coupled database clusters with primary-replica async replication, to the fully tightly-coupled database clusters with NDB Cluster (MySQL/Oracle).

Adding components like ProxySQL to the architecture can, from one side, help in improving high availability, and from the other, it can amplify and randomize the negative effect of a …

In real life, there are frequent cases where getting a running application to work correctly is strongly dependent on consistent write/read operations. This is no issue when using a single data node as a provider, but it becomes more concerning and challenging when adding additional nodes for high availability and/or read scaling.

In the MySQL dimension, I have already described it here in my blog Dirty Reads in High Availability Solution.

We go from the most loosely-coupled database clusters with primary-replica async replication, to the fully tightly-coupled database clusters with NDB Cluster (MySQL/Oracle).

Adding components like ProxySQL to the architecture can, from one side, help in improving high availability, and from the other, it can amplify and randomize the negative effect of a …

As proven again very recently by my colleague and friend Dimitri K, with the TPCC “Mystery”, sysbench made by a former colleague and friend Alexey K, is really the recommended framework to benchmark your system.

I use sysbench of course to benchmark MySQL but also my OS and hardware capabilities.

For those willing to benchmark MySQL 8.0 with sysbench using all supported authentication methods including of course the much more secure default one, caching_sha2_password, you need to compile sysbench using the MySQL libs.

And …

The Percona Kubernetes Operator for Percona XtraDB Cluster(PXC) comes with ProxySQL as part of the deal. And to be honest, the behavior of ProxySQL is pretty much the same as in a regular non-k8s deployment of it. So why bother to write a blog about it? Because what happens around ProxySQL in the context of the operator is actually interesting.

ProxySQL is deployed on its own POD (that can be scaled as well as the PXC Pods can). Each ProxySQL Pod has its own ProxySQL Container and a sidecar container. If you are curious, you can find out which node holds the pod by running

kubectl describe pod cluster1-proxysql-0 | grep Node:
Node: ip-192-168-37-111.ec2.internal/192.168.37.111

Login into and ask for the running containers. You will see something like this:

[root@ip-192-168-37-111 ~]# docker ps | grep -i proxysql …