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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=344716&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-344716
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ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 16/Nov/19 00:26
            Start Date: 16/Nov/19 00:26
    Worklog Time Spent: 10m 
      Work Description: pabloem commented on pull request #9953: DO NOT MERGE 
[BEAM-8335] Adds support for multi-output TestStream
URL: https://github.com/apache/beam/pull/9953#discussion_r347054751
 
 

 ##########
 File path: sdks/python/apache_beam/testing/test_stream_test.py
 ##########
 @@ -127,6 +127,118 @@ def process(self, element=beam.DoFn.ElementParam,
 
     p.run()
 
+  def test_multiple_outputs(self):
+    """Tests that the TestStream supports emitting to multiple PCollections."""
+    test_stream = (TestStream()
+                   .advance_watermark_to(5, tag='letters')
+                   .add_elements(['a', 'b', 'c'], tag='letters')
+                   .advance_watermark_to(10, tag='numbers')
+                   .add_elements(['1', '2', '3'], tag='numbers'))
 
 Review comment:
   Maybe add TimestampedValues with timestamps different from the watermark, to 
check that the runner does not override that?
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 344716)
    Time Spent: 30h 20m  (was: 30h 10m)

> 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: 30h 20m
>  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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