CREATE AGGREGATE defines a new aggregate function. Some basic and commonly-used aggregate functions such as count, min, max, sum, avg and so on are already provided in Greenplum Database. 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 types. Two aggregate functions in the same schema can have the same name if they operate on different input types. The name and input data types of an aggregate function must also be distinct from the name and input data types of every ordinary function in the same schema. This behavior is identical to overloading of ordinary function names. See .

A simple aggregate function is made from one, two, or three ordinary functions (which must be IMMUTABLE functions):

• a state transition function sfunc
• an optional final calculation function ffunc
• an optional combine function combinefunc

These functions are used as follows:

Greenplum Database creates a temporary variable of data type stype to hold the current internal state of the aggregate function. At each input row, the aggregate argument values are calculated and the state transition function is invoked with the current state value and the new argument values to calculate a new internal state value. After all the rows have been processed, the final function is invoked once to calculate the aggregate return value. If there is no final function then the ending state value is returned as-is.

You can specify combinefunc as a method for optimizing aggregate execution. By specifying combinefunc, the aggregate can be executed in parallel on segments first and then on the master. When a two-level execution is performed, sfunc is executed on the segments to generate partial aggregate results, and combinefunc is executed on the master to aggregate the partial results from segments. If single-level aggregation is performed, all the rows are sent to the master and sfunc is applied to the rows.

Single-level aggregation and two-level aggregation are equivalent execution strategies. Either type of aggregation can be implemented in a query plan. When you implement the functions combinefunc and sfunc, you must ensure that the invocation of sfunc on the segment instances followed by combinefunc on the master produce the same result as single-level aggregation that sends all the rows to the master and then applies only the sfunc to the rows.

An aggregate function can provide an optional initial condition, 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 non-null input values, the first argument value replaces the state value, and the transition function is invoked at subsequent rows with all non-null input values. This is useful for implementing aggregates like max. Note that this behavior is only available when state_data_type is the same as the first input_data_type. When these types are different, you must supply a non-null initial condition or use a nonstrict transition function.

If the state transition function is not declared STRICT, then it will be called unconditionally at each input row, and must deal with NULL inputs and NULL transition 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. (This is 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 Moving-Aggregate Mode in the PostgreSQL documentation. This requires specifying the msfunc, minfunc, and mstype functions, and optionally the mspace, mfinalfunc, mfinalfunc_extra, and minitcond functions. Except for minvfunc, these functions work like the corresponding simple-aggregate functions 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.

Single argument aggregate functions, such as 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:

must be equivalent to:

Further assumptions are that the aggregate function 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, and the return type, as well as EXECUTE privilege on the transition and final functions.

The ordinary functions used to define a new aggregate function must be defined first. Note that in this release of Greenplum Database, it is required that the sfunc, ffunc, and combinefunc functions used to create the aggregate are defined as IMMUTABLE.

If the value of the Greenplum Database server configuration parameter gp_enable_multiphase_agg is off, only single-level aggregation is performed.

Any compiled code (shared library files) for custom functions must be placed in the same location on every host in your Greenplum Database array (master and all segments). This location must also be in the LD_LIBRARY_PATH so that the server can locate the files.

In previous versions of Greenplum Database, there was a concept of ordered aggregates. Since version 6, any aggregate can be called as an ordered aggregate, using the syntax: name ( arg [ , ... ] [ORDER BY sortspec [ , ...]] )

The ORDERED keyword is accepted for backwards compatibility, but is ignored.

In previous versions of Greenplum Database, the COMBINEFUNC option was called PREFUNC. It is still accepted for backwards compatibility, as a synonym for COMBINEFUNC.

The following simple example creates an aggregate function that computes the sum of two columns.

Before creating the aggregate function, create two functions that are used as the sfunc and combinefunc functions of the aggregate function.

This function is specified as the sfunc function in the aggregate function.

This function is specified as the combinefunc function in the aggregate function.

This CREATE AGGREGATE command creates the aggregate function that adds two columns.

The following commands create a table, adds some rows, and runs the aggregate function.

This EXPLAIN command shows two phase aggregation.

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

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