NAME

       CREATE_AGGREGATE - define a new aggregate function

SYNOPSIS

       CREATE [ OR REPLACE ] AGGREGATE name ( [ argmode ] [ argname ] arg_data_type [ , ... ] ) (
           SFUNC = sfunc,
           STYPE = state_data_type
           [ , SSPACE = state_data_size ]
           [ , FINALFUNC = ffunc ]
           [ , FINALFUNC_EXTRA ]
           [ , FINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE } ]
           [ , COMBINEFUNC = combinefunc ]
           [ , SERIALFUNC = serialfunc ]
           [ , DESERIALFUNC = deserialfunc ]
           [ , INITCOND = initial_condition ]
           [ , MSFUNC = msfunc ]
           [ , MINVFUNC = minvfunc ]
           [ , MSTYPE = mstate_data_type ]
           [ , MSSPACE = mstate_data_size ]
           [ , MFINALFUNC = mffunc ]
           [ , MFINALFUNC_EXTRA ]
           [ , MFINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE } ]
           [ , MINITCOND = minitial_condition ]
           [ , SORTOP = sort_operator ]
           [ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ]
       )

       CREATE [ OR REPLACE ] 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 ]
           [ , FINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE } ]
           [ , INITCOND = initial_condition ]
           [ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ]
           [ , HYPOTHETICAL ]
       )

       or the old syntax

       CREATE [ OR REPLACE ] AGGREGATE name (
           BASETYPE = base_type,
           SFUNC = sfunc,
           STYPE = state_data_type
           [ , SSPACE = state_data_size ]
           [ , FINALFUNC = ffunc ]
           [ , FINALFUNC_EXTRA ]
           [ , FINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE } ]
           [ , COMBINEFUNC = combinefunc ]
           [ , SERIALFUNC = serialfunc ]
           [ , DESERIALFUNC = deserialfunc ]
           [ , INITCOND = initial_condition ]
           [ , MSFUNC = msfunc ]
           [ , MINVFUNC = minvfunc ]
           [ , MSTYPE = mstate_data_type ]
           [ , MSSPACE = mstate_data_size ]
           [ , MFINALFUNC = mffunc ]
           [ , MFINALFUNC_EXTRA ]
           [ , MFINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE } ]
           [ , MINITCOND = minitial_condition ]
           [ , SORTOP = sort_operator ]
       )

DESCRIPTION

       CREATE AGGREGATE defines a new aggregate function.  CREATE OR REPLACE AGGREGATE will
       either define a new aggregate function or replace an existing definition. Some basic and
       commonly-used aggregate functions are included with the distribution; they are documented
       in Section 9.20. If one defines new types or needs an aggregate function not already
       provided, then CREATE AGGREGATE can be used to provide the desired features.

       When replacing an existing definition, the argument types, result type, and number of
       direct arguments may not be changed. Also, the new definition must be of the same kind
       (ordinary aggregate, ordered-set aggregate, or hypothetical-set aggregate) as the old one.

       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 37.12.1. This requires specifying the MSFUNC, MINVFUNC, and MSTYPE parameters, and
       optionally the MSSPACE, MFINALFUNC, MFINALFUNC_EXTRA, MFINALFUNC_MODIFY, 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.

       An aggregate can optionally support partial aggregation, as described in Section 37.12.4.
       This requires specifying the COMBINEFUNC parameter. If the state_data_type is internal,
       it's usually also appropriate to provide the SERIALFUNC and DESERIALFUNC parameters so
       that parallel aggregation is possible. Note that the aggregate must also be marked
       PARALLEL SAFE to enable parallel aggregation.

       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
       supporting 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.

       FINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE }
           This option specifies whether the final function is a pure function that does not
           modify its arguments.  READ_ONLY indicates it does not; the other two values indicate
           that it may change the transition state value. See NOTES below for more detail. The
           default is READ_ONLY, except for ordered-set aggregates, for which the default is
           READ_WRITE.

       combinefunc
           The combinefunc function may optionally be specified to allow the aggregate function
           to support partial aggregation. If provided, the combinefunc must combine two
           state_data_type values, each containing the result of aggregation over some subset of
           the input values, to produce a new state_data_type that represents the result of
           aggregating over both sets of inputs. This function can be thought of as an sfunc,
           where instead of acting upon an individual input row and adding it to the running
           aggregate state, it adds another aggregate state to the running state.

           The combinefunc must be declared as taking two arguments of the state_data_type and
           returning a value of the state_data_type. Optionally this function may be “strict”. In
           this case the function will not be called when either of the input states are null;
           the other state will be taken as the correct result.

           For aggregate functions whose state_data_type is internal, the combinefunc must not be
           strict. In this case the combinefunc must ensure that null states are handled
           correctly and that the state being returned is properly stored in the aggregate memory
           context.

       serialfunc
           An aggregate function whose state_data_type is internal can participate in parallel
           aggregation only if it has a serialfunc function, which must serialize the aggregate
           state into a bytea value for transmission to another process. This function must take
           a single argument of type internal and return type bytea. A corresponding deserialfunc
           is also required.

       deserialfunc
           Deserialize a previously serialized aggregate state back into state_data_type. This
           function must take two arguments of types bytea and internal, and produce a result of
           type internal. (Note: the second, internal argument is unused, but is required for
           type safety reasons.)

       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.

       MFINALFUNC_MODIFY = { READ_ONLY | SHAREABLE | READ_WRITE }
           This option is like FINALFUNC_MODIFY, but it describes the behavior of the
           moving-aggregate final function.

       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).

       PARALLEL = { SAFE | RESTRICTED | UNSAFE }
           The meanings of PARALLEL SAFE, PARALLEL RESTRICTED, and PARALLEL UNSAFE are the same
           as in CREATE FUNCTION (CREATE_FUNCTION(7)). An aggregate will not be considered for
           parallelization if it is marked PARALLEL UNSAFE (which is the default!) or PARALLEL
           RESTRICTED. Note that the parallel-safety markings of the aggregate's support
           functions are not consulted by the planner, only the marking of the aggregate itself.

       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.

       Ordinarily, PostgreSQL functions are expected to be true functions that do not modify
       their input values. However, an aggregate transition function, when used in the context of
       an aggregate, is allowed to cheat and modify its transition-state argument in place. This
       can provide substantial performance benefits compared to making a fresh copy of the
       transition state each time.

       Likewise, while an aggregate final function is normally expected not to modify its input
       values, sometimes it is impractical to avoid modifying the transition-state argument. Such
       behavior must be declared using the FINALFUNC_MODIFY parameter. The READ_WRITE value
       indicates that the final function modifies the transition state in unspecified ways. This
       value prevents use of the aggregate as a window function, and it also prevents merging of
       transition states for aggregate calls that share the same input values and transition
       functions. The SHAREABLE value indicates that the transition function cannot be applied
       after the final function, but multiple final-function calls can be performed on the ending
       transition state value. This value prevents use of the aggregate as a window function, but
       it allows merging of transition states. (That is, the optimization of interest here is not
       applying the same final function repeatedly, but applying different final functions to the
       same ending transition state value. This is allowed as long as none of the final functions
       are marked READ_WRITE.)

       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. This is why use of an aggregate as a window
       function requires that the final function be read-only: it must 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.

       Partial (including parallel) aggregation is currently not supported for ordered-set
       aggregates. Also, it will never be used for aggregate calls that include DISTINCT or ORDER
       BY clauses, since those semantics cannot be supported during partial aggregation.

EXAMPLES

       See Section 37.12.

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))