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       CREATE_AGGREGATE - define a new aggregate function


       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 = sfunc ]
           [ , MINVFUNC = invfunc ]
           [ , MSTYPE = state_data_type ]
           [ , MSSPACE = state_data_size ]
           [ , MFINALFUNC = ffunc ]
           [ , MFINALFUNC_EXTRA ]
           [ , MINITCOND = initial_condition ]
           [ , SORTOP = sort_operator ]


       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

       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

       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
       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

           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


           The name (optionally schema-qualified) of the aggregate function to

           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.

           The name of an argument. This is currently only useful for
           documentation purposes. If omitted, the argument has no name.

           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(*).)

           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.

           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

           The data type for the aggregate's state value.

           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.

           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.

           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.

           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

           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.

           The data type for the aggregate's state value, when using
           moving-aggregate mode.

           The approximate average size (in bytes) of the aggregate's state
           value, when using moving-aggregate mode. This works the same as

           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.

           The initial setting for the state value, when using
           moving-aggregate mode. This works the same as initial_condition.

           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).

           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.


       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.


       See Section 35.10, “User-defined Aggregates”, in the documentation.


       CREATE AGGREGATE is a PostgreSQL language extension. The SQL standard
       does not provide for user-defined aggregate functions.



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