Last quarter of 2021 AWS released Aurora version 3. This new version aligns Aurora with the latest MySQL 8 version porting many of the advantages MySQL 8 has over previous versions.

While this brings a lot of new interesting features for Aurora, what we are going to cover here is to see how DDLs behave when using the ONLINE option. With a quick comparison with what happens in MySQL 8 standard and with Group Replication. 

Tests

All tests were run on an Aurora instance r6g.large with secondary availability zone.
The test was composed by:

        4 connections

• • #1 to perform ddl
  • #2 to perform insert data in the table I am altering
  • #3 to perform insert data on a different table 
  • #4 checking the other node operations

In the Aurora instance, a sysbench …

When one is responsible for promoting application development from Dev through the various environments such as QA, UAT, etc., through Production, it is often useful to ensure that configurations in test environments are comparable to the final production environment.  This is especially true with systems where a team of DBAs manage the servers.

Obviously, the difference in performance could be due to differences in hardware, storage, networking, software configuration, etc.  The question is how does one quickly and efficiently find the differences without having to run a lot of different commands and compare the output.  Fortunately, our Percona Toolkit has a couple of utilities that can make this much easier.  When you are tasked with supporting large numbers of servers, efficiency is paramount and this is where the toolkit can really help you!

You can find more information on the Percona Toolkit here: …

As a best practice before dropping a large table in MySQL, pt-archiver can be used to delete all the records in batches. This helps to avoid a situation where your server may get stalled under certain circumstances.

I recently read a comment from a user saying “The pt-archiver is not working as expected! It is skipping the last record, which seems like a bug.”. Let’s examine pt-archiver’s default behavior and understand why the author of this comment believes that pt-archiver is bugged (Spoiler: It’s not!).

But wait, before continuing on busting the blame, let me clarify why to use pt-archiver before dropping large tables.

When we drop a table in MySQL:

• Table data/index (ibd) and definition (frm) files are removed.
• Triggers are removed.
• Table definition cache is updated by removing the table being dropped.
• InnoDB buffer pool is scanned for associated pages to …

Recently we saw how we can catch audit information using invisible column, JSON data type and triggers in MySQL 8.0:

• Poorman’s MySQL table audit information
• Poorman’s MySQL table audit information – part 2

Of course, the creation of these triggers can quickly become a tedious operation. Once again, MySQL has all what we need to make it simple.

As you may know, it’s impossible to create triggers from store procedure, so using a sys schema function would not be something possible. However, MySQL Shell is again the answer ! It’s very easy to use a python plugin to perform the necessary operations.

I’ve written such example, available on …

Ingress is a resource that is commonly used to expose HTTP(s) services outside of Kubernetes. To have ingress support, you will need an Ingress Controller, which in a nutshell is a proxy. SREs and DevOps love ingress as it provides developers with a self-service to expose their applications. Developers love it as it is simple to use, but at the same time quite flexible.

High-level ingress design looks like this: 

1. Users connect through a single Load Balancer or other Kubernetes service
2. Traffic is routed through Ingress Pod (or Pods for high availability)
   • There are multiple flavors of Ingress Controllers. Some use nginx, some envoy, or other proxies. See a curated list of Ingress Controllers here.
3. Based on HTTP headers traffic is routed …

Where can you find weekly content on all the things PHP, MySQL, the LAMP stack and related frameworks? If you guessed the OpenLampTech newsletter then you’re correct! Let’s dive into this week’s issue…

The Newsletter for PHP and MySQL Developers

Receive a copy of my ebook, “10 MySQL Tips For Everyone”, absolutely free when you subscribe to the OpenLampTech newsletter.

I’m including so much original and curated content in these weekly newsletters, it’s a wonder my email service provider can even deliver them lol.

Let’s see what is in store in this week’s OpenLampTech issue #22:

…

Access patterns intrigue me because it seems that everyone knows what they are and talks about them, but there’s also very little written about them—in MySQL literature, at least. That’s why I set out to enumerate a list of access patterns (specific to MySQL). Since there’s no apparent standard for access patterns, I cannot say how my list measures up, but after spending most my career with MySQL, I know this: it is necessary to consider these access patterns when evaluating and improving MySQL performance. Simply put: you cannot ignore how the application accesses MySQL.

Access patterns intrigue me because it seems that everyone knows what they are and talks about them, but there’s also very little written about them—in MySQL literature, at least. That’s why I set out to enumerate a list of access patterns (specific to MySQL). Since there’s no apparent standard for access patterns, I cannot say how my list measures up, but after spending most my career with MySQL, I know this: it is necessary to consider these access patterns when evaluating and improving MySQL performance. Simply put: you cannot ignore how the application accesses MySQL.

Access patterns intrigue me because it seems that everyone knows what they are and talks about them, but there’s also very little written about them—in MySQL literature, at least. That’s why I set out to enumerate a list of access patterns (specific to MySQL). Since there’s no apparent standard for access patterns, I cannot say how my list measures up, but after spending most my career with MySQL, I know this: it is necessary to consider these access patterns when evaluating and improving MySQL performance. Simply put: you cannot ignore how the application accesses MySQL.

I really enjoyed to dig into the solution I described yesterday in this post, to generate table audit information using invisible columns and triggers.

In this post, I will focus only on the solution using a JSON column to store the audit information.

Yesterday, I wrote that it’s also possible to track all changes an not only the last one but also keep information about what changed.

I wanted to illustrate that with an example, let’s start with the output:

This is exactly what I was looking for !

And of course we can search in that audit information. For example let’s search for all records that have been modified and where the old or new name was/is frederic:

We can verify that indeed that record had frederic as initial value.

Triggers

Compare …