Mysqldump is the most popular logical backup tool for MySQL. It is included in the MySQL distribution, so it’s ready for use on all of the MySQL instances. 

Logical backups are not, however, the fastest nor the most space-efficient way of backing up MySQL databases, but they have a huge advantage over physical backups. 

Physical backups are usually all or nothing type of backups. While it might be possible to create partial backup with Xtrabackup (we described this in one of our previous blog posts), restoring such backup is tricky and …

In my Webinar on Using Percona Monitoring and Management (PMM) for MySQL Troubleshooting, I showed how to use direct queries to ClickHouse for advanced query analysis tasks. In the followup Webinar Q&A, I promised to describe it in more detail and share some queries, so here it goes.

PMM uses ClickHouse to store query performance data which gives us great performance and a very high compression ratio. ClickHouse stores data in column-store format so it handles denormalized data very well. As a result, all query performance data is stored in one simple “metrics” table:

More and more people are nowadays thinking of cloud migration. The question of “Which cloud provider performs better for my MySQL workload?” is really common but cannot always be easily answered. However, there are ways to come up with an answer. This question also applies when thinking of moving to any provider, not necessarily a cloud one or DBaaS.

The Problem

The most reliable conclusion can be found if you have a testing environment that is fully identical and can produce the same amount of traffic compared to your production version. In this case, the comparison should be straightforward as what you have to do is point your testing environment against the under-evaluation (cloud) providers, and evaluate the differences in performance. But this is not always easy, as many organizations do not have such environments or it’s not always possible to replay all traffic.

The Idea

In this …

Thanks to everyone who joined us last week for this webinar hosted by Database Trends & Technologies (DBTA) and presented by Continuent CEO Eero Teerikorpi. The replay is now available to watch:

How to build a $10M SaaS business into a $6B Unicorn with MySQL and Continuent Tungsten

In this webinar, Eero walks us through the 10-year story of a marketing analytics SaaS, which grew with help from MySQL and Continuent from $10M to be a $6B behemoth: a real SaaS unicorn; and covers a number of related use cases also.

SaaS has emerged as the best way to deliver software, and SaaS solutions, at their best, …

We are all impacted by COVID-19.  On my side, this virus disrupted my travel, professional and personal plans for the upcoming months.  To overcome these disruptions, and following the idea of someone on MySQL Community Slack, I am experimenting with giving MySQL advice on a 30-minute basis.  You can book a slot using this link:

https://jfg-mysql.blogspot.com/p/jfg-mysql-advice-during-covid-19.

MySQL have the nice feature, which helps to write the error log with JSON format . This can be achieved through the MySQL components . In this blog, I am going to show the complete walkthrough involved in this process .

What is MySQL component ?

from MySQL document ,

MySQL Server includes a component-based infrastructure for extending server capabilities. A component provides services that are available to the server and other components. (With respect to service use, the server is a component, equal to other components.) Components interact with each other only through the services they provide.

Link : https://dev.mysql.com/doc/refman/8.0/en/server-components.html

How to enable the JSON logging ?

Step 1 : ( Installing the component ) :

…

Data security plays a major role in current age. Privacy matters a lot. Data masking is one of the Key Features when comes to security.

• In MySQL community versions if you want to mask your data, You can go with a Maxscale load balancer.
• They introduced a new masking filter on the Maxscale 2.1 version.
• My colleague Prasanth written about column-level data masking. For reference click here Column Level Data Masking.
• In MySQL 8.0 Enterprise they have introduced a new security feature called data masking.
• This feature was introduced in MySQL 8.0.13 Enterprise Edition and it provides data masking and de-identification capabilities.

What is Masking ?

• Transformation of existing data to mask it and remove …

MySQL Audit Logging — How to Avoid Data Overload

In the last few months, our solution engineers have had many discussions with security and operation teams about how to implement MySQL auditing. In some cases, these teams have been asked to implement new database auditing in response to a security breach or to meet a regulatory requirement (PCI, HIPPA, GDPR or CCPA).

More often, however, these companies are switching audit strategies because their existing method has led to data overload. They typically start by monitoring everything, sometimes even using the general query log. They quickly learn that even with moderate database activity, the amount of generated data soon becomes overwhelming.

Below are a couple considerations for selecting your audit strategy.

1. Review your schema and identify data that *must* be audited. It’s likely your company’s personal identifiable information (PII) …

Disclaimer: The following blog post does not try to provide a solution for split-brain situations, and the example provided is for demonstrative purposes only. Inconsistencies resulting from a split-brain scenario might possibly be more complex than the one shown, so do not use the following example as a complete guide.

What is Split-Brain?

A split-brain scenario is the result of two data sets (which were originally synced) losing the ability to sync while potentially continuing to receive DMLs over the same rows and ids on both sides. This could have consequences such as data corruption or inconsistencies where each side has data that does not exist on the other side.

For example before split-brain:

After split-brain:

Node1:

Node2:

It can be seen that after the split-brain scenario there are many differences between the nodes:

• Customer row id=2 was deleted …

What You May Not Know About Random Number Generation in Sysbench

Sysbench is a well known and largely used tool to perform benchmarking. Originally written by Peter Zaitsev in early 2000, it has become a de facto standard when performing testing and benchmarking. Nowadays it is maintained by Alexey Kopytov and can be found in Github at https://github.com/akopytov/sysbench.

What I have noticed though, is that while widely-used, some aspects of sysbench are not really familiar to many. For instance, the easy way to expand/modify the MySQL tests is using the lua extension, or the embedded way it handles the random number generation. 

Why This Article? 

I wrote this article with the intent to show how easy it can be to customize sysbench to make it what you need. There are many different ways to extend sysbench use, and one of these is …