Aggregate functions compute a single result from a set of input values. The built-in normal aggregate functions are listed in Table 9.49, “General-Purpose Aggregate Functions” and Table 9.50, “Aggregate Functions for Statistics”. The built-in ordered-set aggregate functions are listed in Table 9.51, “Ordered-Set Aggregate Functions” and Table 9.52, “Hypothetical-Set Aggregate Functions”. The special syntax considerations for aggregate functions are explained in the section called “Aggregate Expressions”. Consult the section called “Aggregate Functions” for additional introductory information.
Table 9.49. General-Purpose Aggregate Functions
Function | Argument Type(s) | Return Type | Description |
---|---|---|---|
array_agg(
| any | array of the argument type | input values, including nulls, concatenated into an array |
avg(
| smallint, int, bigint, real, double precision, numeric, or interval | numeric for any integer-type argument, double precision for a floating-point argument, otherwise the same as the argument data type | the average (arithmetic mean) of all input values |
bit_and(
| smallint, int, bigint, or bit | same as argument data type | the bitwise AND of all non-null input values, or null if none |
bit_or(
| smallint, int, bigint, or bit | same as argument data type | the bitwise OR of all non-null input values, or null if none |
bool_and(
| bool | bool | true if all input values are true, otherwise false |
bool_or(
| bool | bool | true if at least one input value is true, otherwise false |
count(*)
| bigint | number of input rows | |
count( | any | bigint | number of input rows for which the value of expression is not null
|
every(
| bool | bool | equivalent to bool_and |
json_agg(
| any | json | aggregates values as a JSON array |
json_object_agg(
| (any, any) | json | aggregates name/value pairs as a JSON object |
max(
| any array, numeric, string, or date/time type | same as argument type | maximum value of expression across all input
values
|
min(
| any array, numeric, string, or date/time type | same as argument type | minimum value of expression across all input
values
|
string_agg(
| (text, text) or (bytea, bytea) | same as argument types | input values concatenated into a string, separated by delimiter |
sum(
| smallint, int, bigint, real, double precision, numeric, interval, or money | bigint for smallint or int arguments, numeric for bigint arguments, otherwise the same as the argument data type | sum of expression across all input values |
xmlagg(
| xml | xml | concatenation of XML values (see also the section called “xmlagg ”) |
It should be noted that except for count
,
these functions return a null value when no rows are selected. In
particular, sum
of no rows returns null, not
zero as one might expect, and array_agg
returns null rather than an empty array when there are no input
rows. The coalesce
function can be used to
substitute zero or an empty array for null when necessary.
Boolean aggregates bool_and
and
bool_or
correspond to standard SQL aggregates
every
and any
or
some
.
As for any
and some
,
it seems that there is an ambiguity built into the standard syntax:
SELECT b1 = ANY((SELECT b2 FROM t2 ...)) FROM t1 ...;
Here ANY
can be considered either as introducing
a subquery, or as being an aggregate function, if the subquery
returns one row with a Boolean value.
Thus the standard name cannot be given to these aggregates.
Users accustomed to working with other SQL database management
systems might be disappointed by the performance of the
count
aggregate when it is applied to the
entire table. A query like:
SELECT count(*) FROM sometable;
will require effort proportional to the size of the table: PostgreSQL™ will need to scan either the entire table or the entirety of an index which includes all rows in the table.
The aggregate functions array_agg
,
json_agg
,
json_object_agg
,
string_agg
,
and xmlagg
, as well as similar user-defined
aggregate functions, produce meaningfully different result values
depending on the order of the input values. This ordering is
unspecified by default, but can be controlled by writing an
ORDER BY
clause within the aggregate call, as shown in
the section called “Aggregate Expressions”.
Alternatively, supplying the input values from a sorted subquery
will usually work. For example:
SELECT xmlagg(x) FROM (SELECT x FROM test ORDER BY y DESC) AS tab;
But this syntax is not allowed in the SQL standard, and is not portable to other database systems.
Table 9.50, “Aggregate Functions for Statistics” shows
aggregate functions typically used in statistical analysis.
(These are separated out merely to avoid cluttering the listing
of more-commonly-used aggregates.) Where the description mentions
N
, it means the
number of input rows for which all the input expressions are non-null.
In all cases, null is returned if the computation is meaningless,
for example when N
is zero.
Table 9.50. Aggregate Functions for Statistics
Table 9.51, “Ordered-Set Aggregate Functions” shows some aggregate functions that use the ordered-set aggregate syntax. These functions are sometimes referred to as “inverse distribution” functions.
Table 9.51. Ordered-Set Aggregate Functions
All the aggregates listed in Table 9.51, “Ordered-Set Aggregate Functions”
ignore null values in their sorted input. For those that take
a fraction
parameter, the fraction value must be
between 0 and 1; an error is thrown if not. However, a null fraction value
simply produces a null result.
Each of the aggregates listed in
Table 9.52, “Hypothetical-Set Aggregate Functions” is associated with a
window function of the same name defined in
the section called “Window Functions”. In each case, the aggregate result
is the value that the associated window function would have
returned for the “hypothetical” row constructed from
args
, if such a row had been added to the sorted
group of rows computed from the sorted_args
.
Table 9.52. Hypothetical-Set Aggregate Functions
For each of these hypothetical-set aggregates, the list of direct arguments
given in args
must match the number and types of
the aggregated arguments given in sorted_args
.
Unlike most built-in aggregates, these aggregates are not strict, that is
they do not drop input rows containing nulls. Null values sort according
to the rule specified in the ORDER BY
clause.