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 OVER clause.
   
    The rows considered by a window function are those of the “virtual
    table” produced by the query's FROM clause as filtered by its
    WHERE, 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.
     [4]
    Here is an example using sum:
   
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 GROUP BY, HAVING
    and 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);
More details about window functions can be found in Section 4.2.8, Section 9.22, Section 7.2.5, and the SELECT reference page.
[4] There are options to define the window frame in other ways, but this tutorial does not cover them. See Section 4.2.8 for details.