pyflink.datastream.data_stream.AllWindowedStream.reduce

AllWindowedStream.reduce(reduce_function: Union[Callable, pyflink.datastream.functions.ReduceFunction], window_function: Optional[Union[pyflink.datastream.functions.AllWindowFunction, pyflink.datastream.functions.ProcessAllWindowFunction]] = None, output_type: Optional[pyflink.common.typeinfo.TypeInformation] = None) → pyflink.datastream.data_stream.DataStream

Applies the given window function to each window. The window function is called for each evaluation of the window for each key individually. The output of the window function is interpreted as a regular non-windowed stream.

Arriving data is incrementally aggregated using the given reducer.

Example:

>>> ds.window_all(TumblingEventTimeWindows.of(Time.seconds(5))) \
...   .reduce(lambda a, b: a[0] + b[0], b[1])

Parameters

• reduce_function – The reduce function.

• window_function – The window function.

• output_type – Type information for the result type of the window function.

Returns

The data stream that is the result of applying the reduce function to the window.

New in version 1.16.0.