Ever since the release of MySQL 8.0.16, we’ve had the ability to create CHECK constraints in MySQL. At some point, we may want to return a list of CHECK constraints that have been created in a database or against a given table.
Fortunately, we can use the information_schema.check_constraints view to do just that.
We can alternatively use the information_schema.table_constraints view to get the same info.
PostgreSQL has a window function called dense_rank() that returns the rank of the current row, without gaps.
It works the same way that the rank() function works, but without gaps (the rank() function includes gaps).
PostgreSQL has a window function called rank() that returns the rank of the current row, with gaps.
“With gaps” means that it returns the same rank for any ties (i.e. two or more rows with the same value), but then subsequent ranks jump forward to account for the ties.
This means that there’s the potential for noncontiguous rank values. For example it could go 1, 2, 5, etc if several rows are ranked at 2. If there are no ties, then the rank values will be contiguous.
Continue readingIn PostgreSQL, we can use the row_number() function to get each row’s number within its partition. This allows us to create a column with incrementing row numbers that reset with each new partition.
The row_number() function is a window function that’s specifically designed to return the number of the current row within its partition, starting at 1 and incrementing sequentially.
If you’re getting error 3581 in MySQL, which reads “A window which depends on another cannot define partitioning“, it’s probably because you’re using the PARTITION BY clause in a window function that refers to a named window.
To fix this issue, don’t use the PARTITION BY clause when referring to a named window.
When we have a query that returns a column with numerical data such as prices or population, we can use the following methods to automatically calculate the totals and subtotals within a category.
Continue readingMySQL provides us with a wide range of functions for working with JSON documents. Below are four MySQL functions that we can use to get information about JSON values.
Continue readingSQL provides us with an easy way to automatically compute the moving average of a given column.
The moving average (also known as the rolling average, running average, moving mean (MM), or rolling mean) is a series of averages of different selections of the full data set. The moving average changes as we move through the data set. We can add the moving average to our SQL query result sets to see how it changes across the result set.
Continue readingIf you’re getting error 3579 in MySQL, which reads something like “Window name ‘wf3’ is not defined“, it’s probably because you’re referring to a named window that doesn’t exist.
To fix this issue, make sure you refer to a named window that exists.
Continue readingWe can use SQL to create a running total of a given column. By this I mean, we can create a column that calculates the cumulative sum of a given column.
The running total/cumulative sum is the sum of all rows up until the current row. The result is that the sum increases (or decreases in the case of negative values) with each row returned in the result set. Each row’s value is added to the cumulative amount from all prior rows, so for any given row, we get the total sum for all rows up to that point – the “running total”.
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