xenial (7) CREATE_AGGREGATE.7.gz
NAME
CREATE_AGGREGATE - define a new aggregate function
SYNOPSIS
CREATE AGGREGATE name ( [ argmode ] [ argname ] arg_data_type [ , ... ] ) (
SFUNC = sfunc,
STYPE = state_data_type
[ , SSPACE = state_data_size ]
[ , FINALFUNC = ffunc ]
[ , FINALFUNC_EXTRA ]
[ , INITCOND = initial_condition ]
[ , MSFUNC = msfunc ]
[ , MINVFUNC = minvfunc ]
[ , MSTYPE = mstate_data_type ]
[ , MSSPACE = mstate_data_size ]
[ , MFINALFUNC = mffunc ]
[ , MFINALFUNC_EXTRA ]
[ , MINITCOND = minitial_condition ]
[ , SORTOP = sort_operator ]
)
CREATE AGGREGATE name ( [ [ argmode ] [ argname ] arg_data_type [ , ... ] ]
ORDER BY [ argmode ] [ argname ] arg_data_type [ , ... ] ) (
SFUNC = sfunc,
STYPE = state_data_type
[ , SSPACE = state_data_size ]
[ , FINALFUNC = ffunc ]
[ , FINALFUNC_EXTRA ]
[ , INITCOND = initial_condition ]
[ , HYPOTHETICAL ]
)
or the old syntax
CREATE AGGREGATE name (
BASETYPE = base_type,
SFUNC = sfunc,
STYPE = state_data_type
[ , SSPACE = state_data_size ]
[ , FINALFUNC = ffunc ]
[ , FINALFUNC_EXTRA ]
[ , INITCOND = initial_condition ]
[ , MSFUNC = msfunc ]
[ , MINVFUNC = minvfunc ]
[ , MSTYPE = mstate_data_type ]
[ , MSSPACE = mstate_data_size ]
[ , MFINALFUNC = mffunc ]
[ , MFINALFUNC_EXTRA ]
[ , MINITCOND = minitial_condition ]
[ , SORTOP = sort_operator ]
)
DESCRIPTION
CREATE AGGREGATE defines a new aggregate function. Some basic and commonly-used aggregate functions are
included with the distribution; they are documented in Section 9.20, “Aggregate Functions”, in the
documentation. If one defines new types or needs an aggregate function not already provided, then CREATE
AGGREGATE can be used to provide the desired features.
If a schema name is given (for example, CREATE AGGREGATE myschema.myagg ...) then the aggregate function
is created in the specified schema. Otherwise it is created in the current schema.
An aggregate function is identified by its name and input data type(s). Two aggregates in the same schema
can have the same name if they operate on different input types. The name and input data type(s) of an
aggregate must also be distinct from the name and input data type(s) of every ordinary function in the
same schema. This behavior is identical to overloading of ordinary function names (see CREATE FUNCTION
(CREATE_FUNCTION(7))).
A simple aggregate function is made from one or two ordinary functions: a state transition function
sfunc, and an optional final calculation function ffunc. These are used as follows:
sfunc( internal-state, next-data-values ) ---> next-internal-state
ffunc( internal-state ) ---> aggregate-value
PostgreSQL creates a temporary variable of data type stype to hold the current internal state of the
aggregate. At each input row, the aggregate argument value(s) are calculated and the state transition
function is invoked with the current state value and the new argument value(s) to calculate a new
internal state value. After all the rows have been processed, the final function is invoked once to
calculate the aggregate's return value. If there is no final function then the ending state value is
returned as-is.
An aggregate function can provide an initial condition, that is, an initial value for the internal state
value. This is specified and stored in the database as a value of type text, but it must be a valid
external representation of a constant of the state value data type. If it is not supplied then the state
value starts out null.
If the state transition function is declared “strict”, then it cannot be called with null inputs. With
such a transition function, aggregate execution behaves as follows. Rows with any null input values are
ignored (the function is not called and the previous state value is retained). If the initial state value
is null, then at the first row with all-nonnull input values, the first argument value replaces the state
value, and the transition function is invoked at each subsequent row with all-nonnull input values. This
is handy for implementing aggregates like max. Note that this behavior is only available when
state_data_type is the same as the first arg_data_type. When these types are different, you must supply a
nonnull initial condition or use a nonstrict transition function.
If the state transition function is not strict, then it will be called unconditionally at each input row,
and must deal with null inputs and null state values for itself. This allows the aggregate author to have
full control over the aggregate's handling of null values.
If the final function is declared “strict”, then it will not be called when the ending state value is
null; instead a null result will be returned automatically. (Of course this is just the normal behavior
of strict functions.) In any case the final function has the option of returning a null value. For
example, the final function for avg returns null when it sees there were zero input rows.
Sometimes it is useful to declare the final function as taking not just the state value, but extra
parameters corresponding to the aggregate's input values. The main reason for doing this is if the final
function is polymorphic and the state value's data type would be inadequate to pin down the result type.
These extra parameters are always passed as NULL (and so the final function must not be strict when the
FINALFUNC_EXTRA option is used), but nonetheless they are valid parameters. The final function could for
example make use of get_fn_expr_argtype to identify the actual argument type in the current call.
An aggregate can optionally support moving-aggregate mode, as described in Section 35.10.1, “Moving-
Aggregate Mode”, in the documentation. This requires specifying the MSFUNC, MINVFUNC, and MSTYPE
parameters, and optionally the MSSPACE, MFINALFUNC, MFINALFUNC_EXTRA, and MINITCOND parameters. Except
for MINVFUNC, these parameters work like the corresponding simple-aggregate parameters without M; they
define a separate implementation of the aggregate that includes an inverse transition function.
The syntax with ORDER BY in the parameter list creates a special type of aggregate called an ordered-set
aggregate; or if HYPOTHETICAL is specified, then a hypothetical-set aggregate is created. These
aggregates operate over groups of sorted values in order-dependent ways, so that specification of an
input sort order is an essential part of a call. Also, they can have direct arguments, which are
arguments that are evaluated only once per aggregation rather than once per input row. Hypothetical-set
aggregates are a subclass of ordered-set aggregates in which some of the direct arguments are required to
match, in number and data types, the aggregated argument columns. This allows the values of those direct
arguments to be added to the collection of aggregate-input rows as an additional “hypothetical” row.
Aggregates that behave like MIN or MAX can sometimes be optimized by looking into an index instead of
scanning every input row. If this aggregate can be so optimized, indicate it by specifying a sort
operator. The basic requirement is that the aggregate must yield the first element in the sort ordering
induced by the operator; in other words:
SELECT agg(col) FROM tab;
must be equivalent to:
SELECT col FROM tab ORDER BY col USING sortop LIMIT 1;
Further assumptions are that the aggregate ignores null inputs, and that it delivers a null result if and
only if there were no non-null inputs. Ordinarily, a data type's < operator is the proper sort operator
for MIN, and > is the proper sort operator for MAX. Note that the optimization will never actually take
effect unless the specified operator is the “less than” or “greater than” strategy member of a B-tree
index operator class.
To be able to create an aggregate function, you must have USAGE privilege on the argument types, the
state type(s), and the return type, as well as EXECUTE privilege on the transition and final functions.
PARAMETERS
name
The name (optionally schema-qualified) of the aggregate function to create.
argmode
The mode of an argument: IN or VARIADIC. (Aggregate functions do not support OUT arguments.) If
omitted, the default is IN. Only the last argument can be marked VARIADIC.
argname
The name of an argument. This is currently only useful for documentation purposes. If omitted, the
argument has no name.
arg_data_type
An input data type on which this aggregate function operates. To create a zero-argument aggregate
function, write * in place of the list of argument specifications. (An example of such an aggregate
is count(*).)
base_type
In the old syntax for CREATE AGGREGATE, the input data type is specified by a basetype parameter
rather than being written next to the aggregate name. Note that this syntax allows only one input
parameter. To define a zero-argument aggregate function with this syntax, specify the basetype as
"ANY" (not *). Ordered-set aggregates cannot be defined with the old syntax.
sfunc
The name of the state transition function to be called for each input row. For a normal N-argument
aggregate function, the sfunc must take N+1 arguments, the first being of type state_data_type and
the rest matching the declared input data type(s) of the aggregate. The function must return a value
of type state_data_type. This function takes the current state value and the current input data
value(s), and returns the next state value.
For ordered-set (including hypothetical-set) aggregates, the state transition function receives only
the current state value and the aggregated arguments, not the direct arguments. Otherwise it is the
same.
state_data_type
The data type for the aggregate's state value.
state_data_size
The approximate average size (in bytes) of the aggregate's state value. If this parameter is omitted
or is zero, a default estimate is used based on the state_data_type. The planner uses this value to
estimate the memory required for a grouped aggregate query. The planner will consider using hash
aggregation for such a query only if the hash table is estimated to fit in work_mem; therefore, large
values of this parameter discourage use of hash aggregation.
ffunc
The name of the final function called to compute the aggregate's result after all input rows have
been traversed. For a normal aggregate, this function must take a single argument of type
state_data_type. The return data type of the aggregate is defined as the return type of this
function. If ffunc is not specified, then the ending state value is used as the aggregate's result,
and the return type is state_data_type.
For ordered-set (including hypothetical-set) aggregates, the final function receives not only the
final state value, but also the values of all the direct arguments.
If FINALFUNC_EXTRA is specified, then in addition to the final state value and any direct arguments,
the final function receives extra NULL values corresponding to the aggregate's regular (aggregated)
arguments. This is mainly useful to allow correct resolution of the aggregate result type when a
polymorphic aggregate is being defined.
initial_condition
The initial setting for the state value. This must be a string constant in the form accepted for the
data type state_data_type. If not specified, the state value starts out null.
msfunc
The name of the forward state transition function to be called for each input row in moving-aggregate
mode. This is exactly like the regular transition function, except that its first argument and result
are of type mstate_data_type, which might be different from state_data_type.
minvfunc
The name of the inverse state transition function to be used in moving-aggregate mode. This function
has the same argument and result types as msfunc, but it is used to remove a value from the current
aggregate state, rather than add a value to it. The inverse transition function must have the same
strictness attribute as the forward state transition function.
mstate_data_type
The data type for the aggregate's state value, when using moving-aggregate mode.
mstate_data_size
The approximate average size (in bytes) of the aggregate's state value, when using moving-aggregate
mode. This works the same as state_data_size.
mffunc
The name of the final function called to compute the aggregate's result after all input rows have
been traversed, when using moving-aggregate mode. This works the same as ffunc, except that its first
argument's type is mstate_data_type and extra dummy arguments are specified by writing
MFINALFUNC_EXTRA. The aggregate result type determined by mffunc or mstate_data_type must match that
determined by the aggregate's regular implementation.
minitial_condition
The initial setting for the state value, when using moving-aggregate mode. This works the same as
initial_condition.
sort_operator
The associated sort operator for a MIN- or MAX-like aggregate. This is just an operator name
(possibly schema-qualified). The operator is assumed to have the same input data types as the
aggregate (which must be a single-argument normal aggregate).
HYPOTHETICAL
For ordered-set aggregates only, this flag specifies that the aggregate arguments are to be processed
according to the requirements for hypothetical-set aggregates: that is, the last few direct arguments
must match the data types of the aggregated (WITHIN GROUP) arguments. The HYPOTHETICAL flag has no
effect on run-time behavior, only on parse-time resolution of the data types and collations of the
aggregate's arguments.
The parameters of CREATE AGGREGATE can be written in any order, not just the order illustrated above.
NOTES
In parameters that specify support function names, you can write a schema name if needed, for example
SFUNC = public.sum. Do not write argument types there, however — the argument types of the support
functions are determined from other parameters.
If an aggregate supports moving-aggregate mode, it will improve calculation efficiency when the aggregate
is used as a window function for a window with moving frame start (that is, a frame start mode other than
UNBOUNDED PRECEDING). Conceptually, the forward transition function adds input values to the aggregate's
state when they enter the window frame from the bottom, and the inverse transition function removes them
again when they leave the frame at the top. So, when values are removed, they are always removed in the
same order they were added. Whenever the inverse transition function is invoked, it will thus receive the
earliest added but not yet removed argument value(s). The inverse transition function can assume that at
least one row will remain in the current state after it removes the oldest row. (When this would not be
the case, the window function mechanism simply starts a fresh aggregation, rather than using the inverse
transition function.)
The forward transition function for moving-aggregate mode is not allowed to return NULL as the new state
value. If the inverse transition function returns NULL, this is taken as an indication that the inverse
function cannot reverse the state calculation for this particular input, and so the aggregate calculation
will be redone from scratch for the current frame starting position. This convention allows
moving-aggregate mode to be used in situations where there are some infrequent cases that are impractical
to reverse out of the running state value.
If no moving-aggregate implementation is supplied, the aggregate can still be used with moving frames,
but PostgreSQL will recompute the whole aggregation whenever the start of the frame moves. Note that
whether or not the aggregate supports moving-aggregate mode, PostgreSQL can handle a moving frame end
without recalculation; this is done by continuing to add new values to the aggregate's state. It is
assumed that the final function does not damage the aggregate's state value, so that the aggregation can
be continued even after an aggregate result value has been obtained for one set of frame boundaries.
The syntax for ordered-set aggregates allows VARIADIC to be specified for both the last direct parameter
and the last aggregated (WITHIN GROUP) parameter. However, the current implementation restricts use of
VARIADIC in two ways. First, ordered-set aggregates can only use VARIADIC "any", not other variadic array
types. Second, if the last direct parameter is VARIADIC "any", then there can be only one aggregated
parameter and it must also be VARIADIC "any". (In the representation used in the system catalogs, these
two parameters are merged into a single VARIADIC "any" item, since pg_proc cannot represent functions
with more than one VARIADIC parameter.) If the aggregate is a hypothetical-set aggregate, the direct
arguments that match the VARIADIC "any" parameter are the hypothetical ones; any preceding parameters
represent additional direct arguments that are not constrained to match the aggregated arguments.
Currently, ordered-set aggregates do not need to support moving-aggregate mode, since they cannot be used
as window functions.
EXAMPLES
See Section 35.10, “User-defined Aggregates”, in the documentation.
COMPATIBILITY
CREATE AGGREGATE is a PostgreSQL language extension. The SQL standard does not provide for user-defined
aggregate functions.
SEE ALSO
ALTER AGGREGATE (ALTER_AGGREGATE(7)), DROP AGGREGATE (DROP_AGGREGATE(7))