Aggregate Functions

Aggregate functions return a single result row based on groups of rows, rather than on single rows. Aggregate functions can appear in select lists and in ORDER BY and HAVING clauses. They are commonly used with the GROUP BY clause in a SELECT statement, where Oracle Database divides the rows of a queried table or view into groups. In a query containing a GROUP BY clause, the elements of the select list can be aggregate functions, GROUP BY expressions, constants, or expressions involving one of these. Oracle applies the aggregate functions to each group of rows and returns a single result row for each group.

If you omit the GROUP BY clause, then Oracle applies aggregate functions in the select list to all the rows in the queried table or view. You use aggregate functions in the HAVING clause to eliminate groups from the output based on the results of the aggregate functions, rather than on the values of the individual rows of the queried table or view.

See Also:

Using the GROUP BY Clause: Examples and the HAVING Clause for more information on the GROUP BY clause and HAVING clauses in queries and subqueries
Appendix C in Oracle Database Globalization Support Guide for the collation determination rules for expressions in the ORDER BY clause of an aggregate function

Many (but not all) aggregate functions that take a single argument accept these clauses:

DISTINCT and UNIQUE, which are synonymous, cause an aggregate function to consider only distinct values of the argument expression. The syntax diagrams for aggregate functions in this chapter use the keyword DISTINCT for simplicity.
ALL causes an aggregate function to consider all values, including all duplicates.

For example, the DISTINCT average of 1, 1, 1, and 3 is 2. The ALL average is 1.5. If you specify neither, then the default is ALL.

Some aggregate functions allow the windowing_clause, which is part of the syntax of analytic functions. Refer to windowing_clause for information about this clause. In the listing of aggregate functions at the end of this section, the functions that allow the windowing_clause are followed by an asterisk (*)

All aggregate functions except COUNT(*), GROUPING, and GROUPING_ID ignore nulls. You can use the NVL function in the argument to an aggregate function to substitute a value for a null. COUNT and REGR_COUNT never return null, but return either a number or zero. For all the remaining aggregate functions, if the data set contains no rows, or contains only rows with nulls as arguments to the aggregate function, then the function returns null.

The aggregate functions MIN, MAX, SUM, AVG, COUNT, VARIANCE, and STDDEV, when followed by the KEEP keyword, can be used in conjunction with the FIRST or LAST function to operate on a set of values from a set of rows that rank as the FIRST or LAST with respect to a given sorting specification. Refer to FIRST for more information.

You can nest aggregate functions. For example, the following example calculates the average of the maximum salaries of all the departments in the sample schema hr:

SELECT AVG(MAX(salary))
  FROM employees
  GROUP BY department_id;

AVG(MAX(SALARY))
----------------
      10926.3333

This calculation evaluates the inner aggregate (MAX(salary)) for each group defined by the GROUP BY clause (department_id), and aggregates the results again.

In the list of aggregate functions that follows, functions followed by an asterisk (*) allow the windowing_clause.