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.
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