![]() When ORDER BY is omitted the default frame consists of all rows in the 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. Some window functions act only on the rows of the window frame, rather than of the whole partition. 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. It is also possible to omit PARTITION BY, in which case there is a single partition containing all rows. We already saw that ORDER BY can be omitted if the ordering of rows is not important. 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. For example, a row removed because it does not meet the WHERE condition is not seen by any window function. 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. rank needs no explicit parameter, because its behavior is entirely determined by the OVER clause. Rank() OVER (PARTITION BY depname ORDER BY salary DESC)Īs 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. (The window ORDER BY does not even have to match the order in which the rows are output.) Here is an example: 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 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.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |