pyflink.table.udf.udaf

udaf(f: Callable | AggregateFunction | Type, input_types: List[DataType] | DataType | str | List[str] | None = None, result_type: DataType | str | None = None, accumulator_type: DataType | str | None = None, deterministic: bool | None = None, name: str | None = None, func_type: str = 'general') → UserDefinedAggregateFunctionWrapper

udaf(f: None = None, input_types: List[DataType] | DataType | str | List[str] | None = None, result_type: DataType | str | None = None, accumulator_type: DataType | str | None = None, deterministic: bool | None = None, name: str | None = None, func_type: str = 'general') → Callable[[Callable | AggregateFunction | Type], UserDefinedAggregateFunctionWrapper]

Helper method for creating a user-defined aggregate function.

Example

>>> # The input_types is optional.
>>> @udaf(result_type=DataTypes.FLOAT(), func_type="pandas")
... def mean_udaf(v):
...     return v.mean()

>>> # Specify result_type via string
>>> @udaf(result_type='FLOAT', func_type="pandas")
... def mean_udaf(v):
...     return v.mean()

Parameters:

• f – user-defined aggregate function.

• input_types – optional, the input data types.

• result_type – the result data type.

• accumulator_type – optional, the accumulator data type.

• deterministic – the determinism of the function’s results. True if and only if a call to this function is guaranteed to always return the same result given the same parameters. (default True)

• name – the function name.

• func_type – the type of the python function, available value: general, pandas, (default: general)

Returns:

UserDefinedAggregateFunctionWrapper or function.

Added in version 1.12.0.