Window functions are arguably one of [[SQL]]'s more powerful features, allowing us to run powerful aggregations in a very compact syntax, that would require several queries otherwise. According to PostgreSQL documentation: > > A _window function_ performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. 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. Behind the scenes, the window function is able to access more than just the current row of the query result. > ## Examples The most basic example is to run a total: ```sql select task_id, task_group duration_seconds, sum(duration_seconds) over ( partition by task_group order by start_time ) as running_time_per_task from example_schema.example_relation ``` In this example, we can see how the window function is defined by: - A `partition by` clause, that states how to segregate each individual group with columns or expressions, - An `order by` clause, that states how to sort the samples for the aggregation. - A frame clause that defines bounds for the window. ## Resources - [SQL Window Functions cheat sheet](https://learnsql.com/blog/sql-window-functions-cheat-sheet/)