Working on a weekend project,  I became familiar with the SQL keyword “LATERAL”, which I had not used before because it was only introduced recently in MySQL 8.0.14,  so I wanted to share how it can be used.

Some references on this topic:

Lateral Derived Tables

LATERAL Derived Tables in MySQL 8.0

The keyword “LATERAL” comes into play when you work with derived tables. The derived tables have been available in MySQL for a long time, and schematically they look like this:

SELECT t1.foo, t2.bar FROM t1, (SELECT bar FROM table2 WHERE <condition> ) t2 WHERE t1.id=t2.id;

The table “

(SELECT bar FROM table1 …

For this next blog in our Continuent MySQL Use Case series, we’re diving into a sub-series on the topic of ‘multi-master MySQL’.

We’ll cover three (3) multi-master MySQL use cases as part of this sub-series focusing first on e-commerce to start with, and then following up with use cases from financial services and telecommunications.

Multi-master replication for MySQL typically means that a user can write to any master node knowing that the write will be eventually consistent for all nodes in the cluster; unlike regular MySQL replication, where writes have to be applied to the sole master to ensure that it will be synched to all the slaves.

The First Multi-master Customer

The first Continuent multi-master customer is a leading fashion e-commerce company with sites servicing customers across the globe.

More specifically, it has four multi-brand online stores and several online flagship stores …

MySQL has come up with window function in latest GA MySQL 8.0 . It is a major leap in SQL for MySQL. This presentation provides an overview to window function in MySQL 8.0.

Window functions in MySQL 8.0 from Mydbops Window Function in MySQL 8.0

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, flow …

Update 2020-05-05: I stopped providing consulting hours.  They were not very popular, but it was worth trying.

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

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) …