Python's DirectRunner emits multiple panes per window and does not discard late data

The documentation for Beam's Windowing and Triggers functionality [states that](https://beam.apache.org/documentation/programming-guide/#triggers) _"if you use Beam’s default windowing configuration and default trigger, Beam outputs the aggregated result when it estimates all data has arrived, and discards all subsequent data for that window"_. However, it seems that the current behavior of Python's DirectRunner is inconsistent with both of those points. As the `StreamingWordGroupIT.test_discard_late_data` test shows, DirectRunner appears to process every data point that it reads from the input stream, irrespective of whether or not the timestamp of that data point is older than the timestamps of the windows that have already been processed. Furthermore, as the `StreamingWordGroupIT.test_single_output_per_window` test shows, DirectRunner generates multiple "panes" for the same window, apparently disregarding the notion of a watermark?

The Dataflow runner passes both of those end-to-end tests.

Imported from Jira [BEAM-7825](https://issues.apache.org/jira/browse/BEAM-7825). Original Jira may contain additional context.
Reported by: ostrokach.