During many decision-making phases in programming code (conditional logic), there are times execution depends on several different factors. Multiple conditional tests are powerful and constraining, oftentimes requiring more than one test to be passed in order for program flow to proceed. For MySQL (and standard SQL in general) the CASE expression is used for IF/THEN/ELSE conditional logic. The post, MySQL Simple CASE Expression – with examples, covered Simple CASE queries which are essentially equality tests. MySQL Simple CASE is but one variant of 2, with the other being a MySQL Searched CASE Expression.  A MySQL Searched CASE Expression can have multiple conditional tests in each WHEN …

Programming logic is foundational in any application or piece of software. Without it, software wouldn’t really do much of anything. Everything happens off of choice. In the end, some truthy or falsy value is what makes stuff work. For IF/THEN/ELSE logic in standard SQL, there is the CASE expression. There are 2 variations of the CASE Expression: Simple and Searched. In this post, I cover the Simple MySQL CASE expression with example queries…

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Be it running reports or displaying data in some other visualization, SQL SELECT column expressions should be meaningful and understandable. To provide those valuable query results, SQL Developers, use a multitude of available functions, adjacent columns, or other means not readily apparent to end-users. All that being said, the column names often suffer the most as far as readability is concerned, taking on long function call names or other combined expressions. But, as luck would be on our side, there is an easy fix and that is aliasing columns using the AS keyword. Although AS is optional – in this particular context – I err on the side of readability and use it when aliasing SELECT column expressions.

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Each SQL dialect is different in some way, shape, form, or fashion from the next flavor. Some dialects have this function, while others have that function. In this post, I cover porting over Oracle SQL to MySQL in order to count the number of occurrences of a specific weekday found in the current given month (at the time of writing) purely as a learning exercise focused on MySQL DATE functions and the WITH clause…

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I recently published a blog post over on Medium about the differences in 2 versions of the MySQL COUNT() aggregate function: COUNT(*) and COUNT(column_name or expression). I wanted to share the post here with any readers who may be interested so continue reading for more on this post…

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Most developers use some form of auto-incrementing integer counter for a given database table, ensuring uniqueness among the rows. Several of the popular SQL dialects implement this facility. For instance, MySQL’s AUTO_INCREMENT attribute is used to provide a unique identity for a table row. What exactly is the behavior of AUTO_INCREMENT? Can you explicitly use a value of your choosing for it if you need to? How does it count? Continue reading and know the answers to these questions and more…

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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…

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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…

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Rolling sum and average query results are possible by combining the aggregate functions SUM() or AVG() with the OVER() clause, making for powerful analytic queries. I recently learned how to compute a rolling average or sum of values by using the Windowing option of the OVER() clause, applying the concepts to a data set I am familiar with. I wanted to share my learning with any readers who might be interested…

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The Window Ranking functions: ROW_NUMBER(), RANK(), and DENSE_RANK() each rank rows with an increasing integer value. I wrote a previous blog post, ROW_NUMBER() Window Function – find duplicate values, where I covered how the ROW_NUMBER() window function can be used to target any duplicate rows, with the use of the PARTITION BY clause in the OVER() clause. In this post, I cover the differences between RANK(), and DENSE_RANK() in handling any ties according to the sorting performed by the ORDER BY clause with regards to the assigned increasing integer. Continue reading and see examples…

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