damccorm opened a new issue, #19736: URL: https://github.com/apache/beam/issues/19736
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. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
