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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=408985&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-408985
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ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 24/Mar/20 17:54
            Start Date: 24/Mar/20 17:54
    Worklog Time Spent: 10m 
      Work Description: rohdesamuel commented on pull request #11148: 
[BEAM-8335] Adds a streaming wordcount integration test
URL: https://github.com/apache/beam/pull/11148#discussion_r397349737
 
 

 ##########
 File path: 
sdks/python/apache_beam/runners/interactive/interactive_runner_test.py
 ##########
 @@ -147,6 +150,97 @@ def process(self, element):
     ]
     self.assertEqual(actual_reified, expected_reified)
 
+  def test_streaming_wordcount(self):
+    class WordExtractingDoFn(beam.DoFn):
+      def process(self, element):
+        text_line = element.strip()
+        words = text_line.split()
+        return words
+
+    # Add the TestStream so that it can be cached.
+    ib.options.capturable_sources.add(TestStream)
+    ib.options.capture_duration = timedelta(seconds=1)
 
 Review comment:
   Because the background_caching_job is using the real-time clock instead of 
the fake clock from the runner, we limit the capture duration to 1s to limit 
the length of the test.
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 408985)
    Time Spent: 114.5h  (was: 114h 20m)

> 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: 114.5h
>  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



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