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 andHAVING
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
andUNIQUE
, 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 keywordDISTINCT
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.
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.
 APPROX_COUNT
 APPROX_COUNT_DISTINCT
 APPROX_COUNT_DISTINCT_AGG
 APPROX_COUNT_DISTINCT_DETAIL
 APPROX_MEDIAN
 APPROX_PERCENTILE
 APPROX_PERCENTILE_AGG
 APPROX_PERCENTILE_DETAIL
 APPROX_RANK
 APPROX_SUM
 AVG
 COLLECT
 CORR
 CORR_*
 COUNT
 COVAR_POP
 COVAR_SAMP
 CUME_DIST
 DENSE_RANK
 FIRST
 GROUP_ID
 GROUPING
 GROUPING_ID
 JSON_ARRAYAGG
 JSON_OBJECTAGG
 LAST
 LISTAGG
 MAX
 MEDIAN
 MIN
 PERCENT_RANK
 PERCENTILE_CONT
 PERCENTILE_DISC
 RANK
 REGR_ (Linear Regression) Functions
 STATS_BINOMIAL_TEST
 STATS_CROSSTAB
 STATS_F_TEST
 STATS_KS_TEST
 STATS_MODE
 STATS_MW_TEST
 STATS_ONE_WAY_ANOVA
 STATS_T_TEST_*
 STATS_WSR_TEST
 STDDEV
 STDDEV_POP
 STDDEV_SAMP
 SUM
 SYS_OP_ZONE_ID
 SYS_XMLAGG
 TO_APPROX_COUNT_DISTINCT
 TO_APPROX_PERCENTILE
 VAR_POP
 VAR_SAMP
 VARIANCE
 XMLAGG