Chapter 9. Aggregate Functions
Aggregate functions operate on groups of records, rather than on individual records or variables.
They are often used in combination with a GROUP BY
clause.
Syntax
|
<aggregate_function> ::=
| aggragate_function ([<expr> [, <expr> ...]])
| [FILTER (WHERE <condition>)]
The aggregate functions can also be used as window functions with the OVER ()
clause.
See Window (Analytical) Functions for more information.
Aggregate functions are available in DSQL and PSQL. Availability in ESQL is not tracked by this Language Reference.
9.1. FILTER
Clause for Aggregate Functions
The FILTER
clause extends aggregate functions (SUM
, AVG
, COUNT
, etc.) with an additional WHERE
clause.
This limits the rows processed by the aggregate functions to the rows that satisfy the conditions of both the main WHERE
clause and those inside the FILTER
clause.
It can be thought of as a more explicit form of using an aggregate function with a condition (DECODE
, CASE
, IIF
, NULLIF
) to ignore some values that would otherwise be considered by the aggregation.
The FILTER
clause can be used with any aggregate functions in aggregate or windowed (OVER
) statements, but not with window-only functions like DENSE_RANK
.
Example of FILTER
Suppose you need a query to count the rows with status = 'A'
and the row with status = 'E'
as different columns.
The old way to do it would be:
|select count(decode(status, 'A', 1)) status_a,
|count(decode(status, 'E', 1)) status_e
|from data;
The FILTER
clause lets you express those conditions more explicitly:
|select count(*) filter (where status = 'A') status_a,
|count(*) filter (where status = 'E') status_e
|from data;
You can use more than one FILTER
modifier in an aggregate query.
You could, for example, use 12 filters on totals aggregating sales for a year to produce monthly figures for a pivot set.