Exploring SQL without Window Functions (Part I)

What if SQL did not have window functions? Can we even imagine such a world? Window functions are, after all, the heart and soul of SQL’s advanced capabilities. They allow us to perform complex calculations that would be impossible (or at least, highly cumbersome) otherwise.

However, for the sake of this discussion, let’s imagine a world where SQL does not have window functions. What would we miss? What challenges would we face? And how would we attempt to overcome them?

Why Window Functions?

Before diving into a world without window functions, let’s quickly recap why they are so important. Window functions perform a calculation across a set of table rows that are somehow related to the current row. They are like regular SQL aggregate functions (COUNT(), SUM(), AVG(), etc.) but they do not cause rows to become grouped into a single output row like the traditional aggregations.

Common window functions include ROW_NUMBER(), RANK(), DENSE_RANK(), LAG(), LEAD(), and many more. They are extremely useful for tasks such as:

• Comparing current data with historical data (using the LAG/LEAD functions)
• Ranking results within a specific category (using RANK/DENSE_RANK)
• Creating running totals or moving averages (using SUM/AVG with an appropriate window frame)

SQL Without Window Functions

Now, let’s consider what our SQL lives would look like without these handy tools:

Complex Subqueries

Without window functions, we would likely end up writing complex subqueries and self-joins to solve problems like calculating running totals or retrieving lag/lead information. This would not only make our queries harder to read and maintain but also impact performance significantly.

Limited Aggregation

Traditional aggregation functions group rows, returning a single result row for each group. Without window functions, we wouldn’t be able to retain our individual row data alongside these aggregate calculations. This would limit the complexity and depth of analysis we could perform within a single query.

Increased Computation Time

Calculations that are straightforward with window functions would be more computationally expensive without them. Imagine needing to calculate a moving average without the ability to define a frame for your aggregation — the number of computations needed would increase dramatically!

In Part II, we will explore different techniques of how we might approach common use cases, but without Window Functions! Stay tuned! ??????