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PostgreSQL 8.3.23 Documentation
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9.18. Aggregate Functions

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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