In standards-compliant SQL databases, every aggregate function (even user-defined aggregate functions) can be turned into a window function by adding the OVER() clause. | Zoe | Z | 1 | (see this example in action on SQLFiddle) Window functions vs.
The following example creates partitions for every first letter in a first name, similar to a phone book:Īs can be seen below, the COUNT(*) window function counts all people with the same first letter: Instead, you might prefer to PARTITION your data set into several smaller windows. Often, you do not want a single window over your complete data set.
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| Tracey | Zoe | Zoe | (see this example in action on SQLFiddle) Using PARTITION BY to create multiple windows As can be seen in the result, this has a slightly different semantics when it comes to the “first” and “last” records: The above example uses different ORDER BY clauses to access a CURRENT ROW‘s PRECEDING rows, and then just retaining the FIRST_VALUE(). This can be seen in action in an example that is almost equivalent to the previous LEAD() / LAG() examples: Windows can have bounded or unbounded frames as illustrated previously using the PRECEDING and FOLLOWING keywords. (see this example in action on SQLFiddle) Using frame definitions Note that jOOQ makes the above WINDOW clause available to all SQL databases that support window functions, emulating it if it is not natively supported. Furthermore, Sybase SQL Anywhere and PostgreSQL implement the SQL standard WINDOW clause, which allows for avoiding repetitive window definitions. This fact is extremely useful when doing reporting. Such window functions have their own ORDER BY clause, which is independent of the outer query’s ordering. (see this example in action on SQLFiddle) When executing the above, you can immediately see how each record’s FIRST_NAME value can refer to the preceding and following first names: over().orderBy(PEOPLE.FIRST_NAME).as("next")) over().orderBy(PEOPLE.FIRST_NAME).as("prev"), when you want to show the person who’s next to “Leonard”. Within that row’s window, you can then access preceding or following records. In the above example, the processing of a window function might be at the CURRENT ROW, which is “Leonard”‘s row. Once you know window functions, you risk putting them all over the place.Ī window function looks at “windows” of your data while processing it. The low popularity can only be due to developers being oblivious of this cool stuff. One of the coolest features are window functions, whose coolness is in no proportion to their incredibly low popularity. Once you get a hang of the very peculiar syntax, SQL is a highly expressive and rich language offering incredible features at a declarative level.
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