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ASF GitHub Bot logged work on BEAM-8335: ---------------------------------------- Author: ASF GitHub Bot Created on: 06/Mar/20 21:02 Start Date: 06/Mar/20 21:02 Worklog Time Spent: 10m Work Description: robertwb commented on pull request #11005: [BEAM-8335] Modify the StreamingCache to subclass the CacheManager URL: https://github.com/apache/beam/pull/11005#discussion_r389131842 ########## File path: sdks/python/apache_beam/runners/direct/transform_evaluator.py ########## @@ -214,11 +214,31 @@ class _TestStreamRootBundleProvider(RootBundleProvider): """ def get_root_bundles(self): test_stream = self._applied_ptransform.transform + + # The TestStream specification allows for multiple TestStreams in the same + # pipeline (with only one controlling the clock). Here, we use an array in + # the global EvaluationContext state to keep track of the iterator for each + # event stream. + idx = len(self._evaluation_context._test_stream_events) + + # If there was an endpoint defined then get the events from the + # TestStreamService. + if self._evaluation_context._test_stream_endpoint: Review comment: (Regarding the comment above) we should get this from test_stream, rather than plumb it through the context. ---------------------------------------------------------------- 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: 399377) > 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: 100h > 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)