This blog post describes how to use MySQL Autopilot to automate many tasks in MySQL HeatWave Lakehouse, including schema inference, capacity estimation, load time estimation, load script generation, adaptive data sampling, parallel loading of data, and more.

The upcoming tutorial will focus on the ROUND function, which is used to round numeric values for precision and accuracy. Rounding is vital in databases to avoid discrepancies in calculations, particularly with financial and scientific data. The article will provide practical examples and insights into effectively using the ROUND function for reliable results in dbForge Studio for MySQL.

The post MySQL ROUND Function Examples appeared first on Devart Blog.

Writing tests for code that interacts with a database can be daunting. In this post, we discuss how you can easily set up a testing environment using Testcontainers and Node.js and write some tests for code that interacts with a MySQL database.

Testing code that interacts with a database can sometimes be a daunting task. Check out this post about using Testcontainers and Node.js to test code that interacts with a MySQL database.

Every day PlanetScale processes more than 10 billion of our customers’ queries. We need to collect, store, and serve telemetry data generated by these queries to power Insights, our built-in query performance tool. This post describes how we built a scalable telemetry pipeline using Apache Kafka and a sharded PlanetScale database. Insights requirements To show you Insights, we pull from the following datasets: Database-level time series data (e.g., queries per second across the entire database). Query pattern-level time series data (e.g., p95 for a single query pattern like SELECT email FROM users where id = %) Data on specific query executions for slow/expensive queries (the “slow query log”). The database-level data fits well into a time series database like Prometheus, but we run into several issues when trying to store the query-pattern level data in a time series database. On any given day, there are 10s of millions of unique query …

Over the years, I have become obsessed with writing code tests. One big pain point with writing tests is testing code that interacts with a database. In this post, we are going to talk about some of the difficulties that may be encountered when writing tests for database interaction and how we can use Testcontainers to mitigate […]

After discussing with Simon about some issues when trying to recompile MySQL 8.0.34 on CentOS 9 (see #111159), I also tried it and indeed some dependencies are not listed when compiling via the source RPM.

Let’s see how to recompile the two latest versions of MySQL (8.0.34 and 8.1.0) using the source RPMs.

I use Oracle Linux 9 as build machine.

Getting the source RPM

To get the source RPM, you need first to install the MySQL Community’s repo:

$ sudo dnf install …

MySQL 8.0.34 brings us a new password validation parameter. Using this, we can control the minimum number of characters in a password that a user must change before validate_password accepts a new password for the user’s account.

In this blog, I offer a few scenarios showing how the parameter validate_password.changed_characters_percentage affects user password changes.

Requirement

To make this work, we should enable the “Password Verification-Required Policy” (introduced in MySQL 8.0.13). We can allow it to GLOBALLY by using the parameter “password_require_current” or by specifying  “PASSWORD REQUIRE CURRENT” while creating or altering the user. This topic was already explained very well by Brain Sumpter in his post, …

Deferred join is powerful. Deferred join is simple. Deferred join is misunderstood.

Deferred join is powerful. Deferred join is simple. Deferred join is misunderstood.