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ASF GitHub Bot logged work on BEAM-8335: ---------------------------------------- Author: ASF GitHub Bot Created on: 04/Mar/20 19:32 Start Date: 04/Mar/20 19:32 Worklog Time Spent: 10m Work Description: rohdesamuel commented on pull request #11005: [BEAM-8335] Modify the StreamingCache to subclass the CacheManager URL: https://github.com/apache/beam/pull/11005#discussion_r387887355 ########## File path: sdks/python/apache_beam/runners/direct/transform_evaluator.py ########## @@ -421,8 +440,12 @@ def process_element(self, element): main_output = list(self._outputs)[0] bundle = self._evaluation_context.create_bundle(main_output) for tv in event.timestamped_values: - bundle.output( - GlobalWindows.windowed_value(tv.value, timestamp=tv.timestamp)) + # Unreify the value into the correct window. + try: + bundle.output(WindowedValue(**tv.value)) Review comment: Unfortunately the Python SDK interprets an element that's a WindowedValue as an element that should have its windowing information changed. This is used directly by the ReverseTestStream to produce WindowedValue args that keep the windowing information. But if these elements were WindowedValues themselves, then the Python SDK would reinterpret and unnest them at every step. ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: us...@infra.apache.org Issue Time Tracking ------------------- Worklog Id: (was: 397813) Time Spent: 89h 10m (was: 89h) > Add streaming support to Interactive Beam > ----------------------------------------- > > Key: BEAM-8335 > URL: https://issues.apache.org/jira/browse/BEAM-8335 > Project: Beam > Issue Type: Improvement > Components: runner-py-interactive > Reporter: Sam Rohde > Assignee: Sam Rohde > Priority: Major > Time Spent: 89h 10m > Remaining Estimate: 0h > > This issue tracks the work items to introduce streaming support to the > Interactive Beam experience. This will allow users to: > * Write and run a streaming job in IPython > * Automatically cache records from unbounded sources > * Add a replay experience that replays all cached records to simulate the > original pipeline execution > * Add controls to play/pause/stop/step individual elements from the cached > records > * Add ability to inspect/visualize unbounded PCollections -- This message was sent by Atlassian Jira (v8.3.4#803005)