Mastering SQL- Window Functions.
When embarking on a journey in the realm of Data Science or preparing for Data Science interviews, you are bound to encounter window functions, a powerful tool that can unlock new dimensions in your data analysis. In this article, we’ll delve into the world of window functions, demystifying their usage with practical examples and shedding light on their technical intricacies. These functions often surface as challenging problems during interviews, ranging from medium to hard difficulty. So, let’s begin by unraveling the essence of window functions.
What Are Window Functions?
Window functions empower you to perform operations over a selected set of rows within your dataset, with or without partitioning. These operations can encompass a wide array of tasks, including ranking rows, executing cumulative calculations, or even shifting rows. To illustrate this concept, consider a straightforward example:
-- In the given table of salaries, find the job titles of the top 3 employees who received the most overtime pay
-- Without window functions
SELECT title
FROM salaries
ORDER BY overtimerate DESC
LIMIT 3
-- With window function
WITH cte AS (SELECT *, RANK() OVER (ORDER BY overtimerate DESC)
FROM salaries)
SELECT title
FROM cte
WHERE rank <= 3
