3.5. Window Functions
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. However, window functions do not cause rows to become grouped into a single output row like non-window aggregate calls would. Instead, 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.
Here is an example that shows how to compare each employee's salary with the average salary in his or her department:
SELECT depname, empno, salary, avg(salary) OVER (PARTITION BY depname) FROM empsalary;
depname | empno | salary | avg -----------+-------+--------+----------------------- develop | 11 | 5200 | 5020.0000000000000000 develop | 7 | 4200 | 5020.0000000000000000 develop | 9 | 4500 | 5020.0000000000000000 develop | 8 | 6000 | 5020.0000000000000000 develop | 10 | 5200 | 5020.0000000000000000 personnel | 5 | 3500 | 3700.0000000000000000 personnel | 2 | 3900 | 3700.0000000000000000 sales | 3 | 4800 | 4866.6666666666666667 sales | 1 | 5000 | 4866.6666666666666667 sales | 4 | 4800 | 4866.6666666666666667 (10 rows)
The first three output columns come directly from the table
empsalary, and there is one output row for each row in the table. The fourth column represents an average taken across all the table rows that have the same
depname value as the current row. (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.)
A window function call always contains an
OVER clause directly following the window function's name and argument(s). This is what syntactically distinguishes it from a normal function or non-window aggregate. The
OVER clause determines exactly how the rows of the query are split up for processing by the window function. The
PARTITION BY clause within
OVER divides the rows into groups, or partitions, that share the same values of the
PARTITION BY expression(s). For each row, the window function is computed across the rows that fall into the same partition as the current row.
You can also control the order in which rows are processed by window functions using
ORDER BY within
OVER. (The window
ORDER BY does not even have to match the order in which the rows are output.) Here is an example:
SELECT depname, empno, salary, rank() OVER (PARTITION BY depname ORDER BY salary DESC) FROM empsalary;
depname | empno | salary | rank -----------+-------+--------+------ develop | 8 | 6000 | 1 develop | 10 | 5200 | 2 develop | 11 | 5200 | 2 develop | 9 | 4500 | 4 develop | 7 | 4200 | 5 personnel | 2 | 3900 | 1 personnel | 5 | 3500 | 2 sales | 1 | 5000 | 1 sales | 4 | 4800 | 2 sales | 3 | 4800 | 2 (10 rows)
As shown here, the
rank function produces a numerical rank for each distinct
ORDER BY value in the current row's partition, using the order defined by the
ORDER BY clause.
rank needs no explicit parameter, because its behavior is entirely determined by the
The rows considered by a window function are those of the “virtual table” produced by the query's
FROM clause as filtered by its
GROUP BY, and
HAVING clauses if any. For example, a row removed because it does not meet the
WHERE condition is not seen by any window function. A query can contain multiple window functions that slice up the data in different ways using different
OVER clauses, but they all act on the same collection of rows defined by this virtual table.
We already saw that
ORDER BY can be omitted if the ordering of rows is not important. It is also possible to omit
PARTITION BY, in which case there is a single partition containing all rows.
There is another important concept associated with window functions: for each row, there is a set of rows within its partition called its window frame. Some window functions act only on the rows of the window frame, rather than of the whole partition. By default, if
ORDER BY is supplied then the frame consists of all rows from the start of the partition up through the current row, plus any following rows that are equal to the current row according to the
ORDER BY clause. When
ORDER BY is omitted the default frame consists of all rows in the partition.  Here is an example using
SELECT salary, sum(salary) OVER () FROM empsalary;
salary | sum --------+------- 5200 | 47100 5000 | 47100 3500 | 47100 4800 | 47100 3900 | 47100 4200 | 47100 4500 | 47100 4800 | 47100 6000 | 47100 5200 | 47100 (10 rows)
Above, since there is no
ORDER BY in the
OVER clause, the window frame is the same as the partition, which for lack of
PARTITION BY is the whole table; in other words each sum is taken over the whole table and so we get the same result for each output row. But if we add an
ORDER BY clause, we get very different results:
SELECT salary, sum(salary) OVER (ORDER BY salary) FROM empsalary;
salary | sum --------+------- 3500 | 3500 3900 | 7400 4200 | 11600 4500 | 16100 4800 | 25700 4800 | 25700 5000 | 30700 5200 | 41100 5200 | 41100 6000 | 47100 (10 rows)
Here the sum is taken from the first (lowest) salary up through the current one, including any duplicates of the current one (notice the results for the duplicated salaries).
Window functions are permitted only in the
SELECT list and the
ORDER BY clause of the query. They are forbidden elsewhere, such as in
WHERE clauses. This is because they logically execute after the processing of those clauses. Also, window functions execute after non-window aggregate functions. This means it is valid to include an aggregate function call in the arguments of a window function, but not vice versa.
If there is a need to filter or group rows after the window calculations are performed, you can use a sub-select. For example:
SELECT depname, empno, salary, enroll_date FROM (SELECT depname, empno, salary, enroll_date, rank() OVER (PARTITION BY depname ORDER BY salary DESC, empno) AS pos FROM empsalary ) AS ss WHERE pos < 3;
The above query only shows the rows from the inner query having
rank less than 3.
When a query involves multiple window functions, it is possible to write out each one with a separate
OVER clause, but this is duplicative and error-prone if the same windowing behavior is wanted for several functions. Instead, each windowing behavior can be named in a
WINDOW clause and then referenced in
OVER. For example:
SELECT sum(salary) OVER w, avg(salary) OVER w FROM empsalary WINDOW w AS (PARTITION BY depname ORDER BY salary DESC);