The latest from the MySQL community

You ship a query on Monday. It runs in 2 ms. Six months later, the same query — same SQL, same indexes — takes 4 seconds. Nothing changed. Except one thing did: the table grew.

Welcome to the everyday problem Big O was invented to describe. This post is a practical, MySQL-flavoured tour of time complexity. We’ll keep the math light, the pictures clear, and we’ll finish with the exact algorithms your database uses to keep your queries fast (or slow).

What is Big O, really?

Forget seconds. Big O is not a unit of time. It’s a way of describing how the cost of an algorithm grows as the input grows. Specifically: if you double the data, does the work double? Stay the same? Quadruple? That shape is the algorithm’s complexity.

We call the input size n. A few shapes come up over and over in real systems:

• O(1) — …

Yesterday I participated to the Oracle Technology Roundtable for Digital Natives in Zurich.

It was a good opportunity to learn more about AI, Cloud and HeatWave with the focus on very trendy features of this product: generative AI, machine learning, vector processing, analytics and transaction processing across data in Data Lake and MySQL databases.

It was also great to share moments with the Oracle and MySQL teams and meet customers which gave feedback and tips about their solutions already in place in this area.

I’ll try to summarize below some key take-away of each session.

Unlocking Innovation: How Oracle AI is Shaping the Future of Business (by Jürgen Wirtgen)

AI is not a new topic. But how do we …

We know that SQL statement compatibility can change with major database version upgrades and that you should adequately test for them. But what about minor version upgrades?

It is dangerous to assume that your existing SQL statements work with a minor update, especially when using an augmented version of an open-source database such as a cloud provider that may not be as transparent about all changes.

While I have always found reading the release notes an important step in architectural principles over the decades, many organizations skip over this principle and get caught off guard when there are no dedicated DBAs and architects in the engineering workforce.

Real-world examples of minor version upgrade issues

Here are two real-world situations common in the AWS RDS ecosystem using MySQL.

1. You are an organization that uses RDS Aurora MySQL for its production systems, and you upgrade one minor version …

I continue to dig up and share this simple approach for production data masking via SQL to create testing data sets. Time to codify it into a post.

Rather than generating a set of names and data from tools such as Mockaroo, it is more practical to use actual data for a variety of testing reasons.

The SQL below is a self-explanatory approach of removing Personal Identifiable Information (PII), but keeping data relevant. I use this approach for a number of reasons.

• We are using production data rather than synthetic data. Data volume, distribution, and additional column values are realistic. This is a subset of an example, but dates and locations are therefore realistic
• Indexes (and unique indexes) still work, and distribution across the index is adequate for searching. Technically the index …

MySQL is a traditional open source relational database that goes well with many well-established applications. Find out more about its features and use cases.

CSV or SQL? SQL or CSV? How about together? Without a doubt, CSV’s are one of the most common and familiar data interchange formats. Importing and exporting CSV data into or out of an SQL database is a staple process in most every data workflow. I’ve written numerous blog posts on both importing and exporting CSV data in an SQL environment. In this post, I am including all of these specific posts (as of the time of writing) in one easy-to-read and centralized location…

Image by xresch from  …

In the last post I covered some of the many reasons to migrate data from a spreadsheet to a database and now it is time to show how to do just that.  Moving data from a spreadsheet into MySQL can actually be pretty simple in many cases. Now I will not mislead you by telling you that all cases are easy but there is an easy way to make this migration.  And I highly recommend the following process when possible as it can save lots of time. More painful migrations will be covered in the future but this post is my favorite 'fast and easy' process.

This is a guide to taking data from a spreadsheet and easily moving that data into a MySQL database instance. The trick is the Import Wizard in MySQL Workbench that does a lot of the detail work for you. In a future post we will go into what you have to do when you are not …

CSV imports with MySQL Workbench, is super simple. Since CSV’s are probably the most common data interchange format, it goes without saying that importing CSV data into MySQL is a staple task for all DBA’s and Developers. Continue reading to learn how easy it is using MySQL Workbench…

Image by OpenClipart-Vectors from Pixabay

Self-Promotion:

If you enjoy the content written here, by all means, …

If you use SQL on a regular basis, then you are well aware that Window Functions are powerful. They allow us to simplify queries that would otherwise be quite the mess. We can provide meaningful insight across rows of data without collapsing the results into a single value. I have written numerous blog posts on Window Functions, many here recently. I decided to make this blog post a compilation of all the Window Function posts I have written, providing a one-stop source for any readers interested in learning more about Window Functions…

Image by Free-Photos from …

Top n Window Function queries over a specific subset of data are common in analysis and reporting requirements. Luckily, in MySQL, there are Window functions we can use for this type of query. To be quite honest, you don’t necessarily need Window Functions. You can retrieve those top 3 (or whatever) types of results with a regular SQL query. But, since we have those powerful Window Functions, why not use them? My thoughts exactly! Besides, no one wants a spaghetti code mess of SQL to try and understand. Not to mention, Window functions are often better optimized for querying larger data sets. Continue reading and see example queries for more understanding…

Image by …