CREATE AGGREGATE — define a new aggregate function
CREATE AGGREGATEname
( [argmode
] [argname
]arg_data_type
[ , ... ] ) ( SFUNC =sfunc
, STYPE =state_data_type
[ , SSPACE =state_data_size
] [ , FINALFUNC =ffunc
] [ , FINALFUNC_EXTRA ] [ , 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 ] [ , MINITCOND =minitial_condition
] [ , SORTOP =sort_operator
] [ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ] ) CREATE AGGREGATEname
( [ [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
] [ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ] [ , HYPOTHETICAL ] ) or the old syntax CREATE AGGREGATEname
( BASETYPE =base_type
, SFUNC =sfunc
, STYPE =state_data_type
[ , SSPACE =state_data_size
] [ , FINALFUNC =ffunc
] [ , FINALFUNC_EXTRA ] [ , 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 ] [ , MINITCOND =minitial_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. 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-stateffunc
( 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 37.10.1.
This requires specifying the MSFUNC
,
MINVFUNC
, and MSTYPE
parameters, and optionally the MSPACE
, 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.
An aggregate can optionally support partial aggregation, as described in Section 37.10.4. 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.
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.
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.
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
The meanings of PARALLEL SAFE
,
PARALLEL RESTRICTED
, and PARALLEL UNSAFE
are the same as for CREATE
FUNCTION. 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.
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.
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.
See Section 37.10.
CREATE AGGREGATE
is a PostgreSQL language extension. The SQL
standard does not provide for user-defined aggregate functions.
If you see anything in the documentation that is not correct, does not match your experience with the particular feature or requires further clarification, please use this form to report a documentation issue.