But unlike regular aggregate functions, use of a window function does not cause rows to become grouped into a single output row - the rows retain their separate identities. This is comparable to the type of calculation that can be done with an aggregate function. PostgreSQL’s documentation does a good job introducing the concept:Ī window function performs a calculation across a set of table rows that are somehow related to the current row. These functions provide a convenient way to compute complex results using a simple, declarative syntax, and can be used to solve a wide range of problems. SQL window functions are a powerful feature of SQL that allow users to perform calculations across a set of rows, or 'window', in a query. It is a must know for software engineers and data scientists.

Window functions are an example of one such SQL concept. Even though the tools differ in the types of problems they were designed to solve, they employ the fundamentals of SQL, which makes it slightly easier for people to work with big data. Today we have multiple tools like Hive and Spark to handle Big Data.

In 2022, the world produced and consumed 94 zetabytes of data. Data is proliferating at an astonishing rate. This article is a guide on using SQL window functions in applications that need to make computational heavy queries.