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Aggregate functions compute a single result
value from a set of input values. The built-in aggregate functions
are listed in
Table 9-41 and
Table 9-42.
The special syntax considerations for aggregate
functions are explained in Section 4.2.7.
Consult Section 2.7 for additional introductory
information.
Table 9-41. General-Purpose Aggregate Functions | Function | Argument Type | Return Type | Description |
|---|
avg(expression)
| 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(expression)
| 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(expression)
| 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(expression)
| bool
| bool
| true if all input values are true, otherwise false |
bool_or(expression)
| bool
| bool
| true if at least one input value is true, otherwise false | count(*) | | bigint | number of input rows | count(expression) | any | bigint | number of input rows for which the value of expression is not null
|
every(expression)
| bool
| bool
| equivalent to bool_and | max(expression) | any array, numeric, string, or date/time type | same as argument type | maximum value of expression across all input
values
| min(expression) | any array, numeric, string, or date/time type | same as argument type | minimum value of expression across all input
values
| sum(expression) | smallint, int,
bigint, real, double
precision, numeric, or
interval
| bigint for smallint or
int arguments, numeric for
bigint arguments, double precision
for floating-point arguments, otherwise the same as the
argument data type
| sum of expression across all input values |
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. The coalesce function can be
used to substitute zero for null when necessary.
Note: 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 both as leading
to a subquery or as an aggregate if the select expression returns 1 row.
Thus the standard name cannot be given to these aggregates.
Note: Users accustomed to working with other SQL database management
systems might be surprised by the performance of the
count aggregate when it is applied to the
entire table. A query like:
SELECT count(*) FROM sometable;
will be executed by PostgreSQL using a
sequential scan of the entire table.
Table 9-42 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 9-42. Aggregate Functions for Statistics | Function | Argument Type | Return Type | Description |
|---|
corr(Y, X)
| double precision
| double precision
| correlation coefficient |
covar_pop(Y, X)
| double precision
| double precision
| population covariance |
covar_samp(Y, X)
| double precision
| double precision
| sample covariance | regr_avgx(Y, X)
| double precision
| double precision
| average of the independent variable
(sum(X)/N) | regr_avgy(Y, X)
| double precision
| double precision
| average of the dependent variable
(sum(Y)/N) | regr_count(Y, X)
| double precision
| bigint
| number of input rows in which both expressions are nonnull |
regr_intercept(Y, X)
| double precision
| double precision
| y-intercept of the least-squares-fit linear equation
determined by the (X, Y) pairs | regr_r2(Y, X)
| double precision
| double precision
| square of the correlation coefficient |
regr_slope(Y, X)
| double precision
| double precision
| slope of the least-squares-fit linear equation determined
by the (X,
Y) pairs | regr_sxx(Y, X)
| double precision
| double precision
| sum(X^2) - sum(X)^2/N ("sum of
squares" of the independent variable) | regr_sxy(Y, X)
| double precision
| double precision
| sum(X*Y) - sum(X) * sum(Y)/N ("sum of
products" of independent times dependent
variable) | regr_syy(Y, X)
| double precision
| double precision
| sum(Y^2) - sum(Y)^2/N ("sum of
squares" of the dependent variable) |
stddev(expression)
| smallint, int,
bigint, real, double
precision, or numeric
| double precision for floating-point arguments,
otherwise numeric
| historical alias for stddev_samp |
stddev_pop(expression)
| smallint, int,
bigint, real, double
precision, or numeric
| double precision for floating-point arguments,
otherwise numeric
| population standard deviation of the input values |
stddev_samp(expression)
| smallint, int,
bigint, real, double
precision, or numeric
| double precision for floating-point arguments,
otherwise numeric
| sample standard deviation of the input values |
variance(expression)
| smallint, int,
bigint, real, double
precision, or numeric
| double precision for floating-point arguments,
otherwise numeric
| historical alias for var_samp |
var_pop(expression)
| smallint, int,
bigint, real, double
precision, or numeric
| double precision for floating-point arguments,
otherwise numeric
| population variance of the input values (square of the population standard deviation) |
var_samp(expression)
| smallint, int,
bigint, real, double
precision, or numeric
| double precision for floating-point arguments,
otherwise numeric
| sample variance of the input values (square of the sample standard deviation) |
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