CREATE AGGREGATE

CREATE AGGREGATE

7

SQL - Language Statements

CREATE AGGREGATE

define a new aggregate function

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 [???](#functions-aggregate). 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
[???](#sql-createfunction)).

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 [???](#xaggr-moving-aggregates). 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
[???](#xaggr-partial-aggregates). 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.

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](#sql-createaggregate-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`](#sql-createfunction). 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 {#sql-createaggregate-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 MDASH 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 [???](#xaggr).

Compatibility
=============

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

See Also
========
