You can also control the order in which rows are processed by window functions using ORDER BY within OVER. For each row, the window function is computed across the rows that fall into the same partition as the current row. The PARTITION BY clause within OVER divides the rows into groups, or partitions, that share the same values of the PARTITION BY expression(s). The OVER clause determines exactly how the rows of the query are split up for processing by the window function. This is what syntactically distinguishes it from a normal function or non-window aggregate. (This actually is the same function as the non-window avg aggregate, but the OVER clause causes it to be treated as a window function and computed across the window frame.)Ī window function call always contains an OVER clause directly following the window function's name and argument(s). The fourth column represents an average taken across all the table rows that have the same depname value as the current row. The first three output columns come directly from the table empsalary, and there is one output row for each row in the table. SELECT depname, empno, salary, avg(salary) OVER (PARTITION BY depname) FROM empsalary
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Here is an example that shows how to compare each employee's salary with the average salary in his or her department: Behind the scenes, the window function is able to access more than just the current row of the query result. Instead, the rows retain their separate identities. However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would. This is comparable to the type of calculation that can be done with an aggregate function. A window function performs a calculation across a set of table rows that are somehow related to the current row.
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