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https://issues.apache.org/jira/browse/BEAM-7926?focusedWorklogId=353116&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-353116
]
ASF GitHub Bot logged work on BEAM-7926:
----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Dec/19 23:51
Start Date: 03/Dec/19 23:51
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #10276: [BEAM-7926]
Data-centric Interactive Part1
URL: https://github.com/apache/beam/pull/10276#discussion_r353484078
##########
File path:
sdks/python/apache_beam/runners/interactive/display/pipeline_graph_test.py
##########
@@ -83,6 +91,45 @@ def test_get_dot(self):
'}\n'),
pipeline_graph.PipelineGraph(p).get_dot())
+ @patch('IPython.get_ipython', mock_get_ipython)
+ def test_get_dot_within_notebook(self):
+ # Assume a mocked ipython kernel and notebook frontend have been set up.
+ ie.current_env()._is_in_ipython = True
+ ie.current_env()._is_in_notebook = True
+ with mock_get_ipython(): # Cell 1
+ p = beam.Pipeline(ir.InteractiveRunner())
+ # Immediately track this local pipeline so that ipython prompts when
+ # applying transforms will be tracked and used for labels.
+ ib.watch(locals())
+
+ with mock_get_ipython(): # Cell 2
+ init_pcoll = p | 'Init' >> beam.Create(range(10))
+
+ with mock_get_ipython(): # Cell 3
+ squares = init_pcoll | 'Square' >> beam.Map(lambda x: x * x)
+
+ with mock_get_ipython(): # Cell 4
+ cubes = init_pcoll | 'Cube' >> beam.Map(lambda x: x ** 3)
+
+ # Tracks all PCollections defined so far.
+ ib.watch(locals())
+ self.assertEqual(
+ ('digraph G {\n'
+ 'node [color=blue, fontcolor=blue, shape=box];\n'
+ '"Cell 2: Init";\n'
+ 'init_pcoll [shape=circle];\n'
+ '"Cell 3: Square";\n'
+ 'squares [shape=circle];\n'
+ '"Cell 4: Cube";\n'
+ 'cubes [shape=circle];\n'
+ '"Cell 2: Init" -> init_pcoll;\n'
+ 'init_pcoll -> "Cell 3: Square";\n'
+ 'init_pcoll -> "Cell 4: Cube";\n'
+ '"Cell 3: Square" -> squares;\n'
+ '"Cell 4: Cube" -> cubes;\n'
+ '}\n'),
Review comment:
`Create` is a composite transform. The dot based pipeline graph only renders
top-level transform and our label altering only happens to top-level
transforms. So whether a transform is composite or not doesn't affect either.
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Issue Time Tracking
-------------------
Worklog Id: (was: 353116)
Time Spent: 22h 20m (was: 22h 10m)
> Show PCollection with Interactive Beam in a data-centric user flow
> ------------------------------------------------------------------
>
> Key: BEAM-7926
> URL: https://issues.apache.org/jira/browse/BEAM-7926
> Project: Beam
> Issue Type: New Feature
> Components: runner-py-interactive
> Reporter: Ning Kang
> Assignee: Ning Kang
> Priority: Major
> Time Spent: 22h 20m
> Remaining Estimate: 0h
>
> Support auto plotting / charting of materialized data of a given PCollection
> with Interactive Beam.
> Say an Interactive Beam pipeline defined as
>
> {code:java}
> p = beam.Pipeline(InteractiveRunner())
> pcoll = p | 'Transform' >> transform()
> pcoll2 = ...
> pcoll3 = ...{code}
> The use can call a single function and get auto-magical charting of the data.
> e.g.,
> {code:java}
> show(pcoll, pcoll2)
> {code}
> Throughout the process, a pipeline fragment is built to include only
> transforms necessary to produce the desired pcolls (pcoll and pcoll2) and
> execute that fragment.
> This makes the Interactive Beam user flow data-centric.
>
> Detailed
> [design|https://docs.google.com/document/d/1DYWrT6GL_qDCXhRMoxpjinlVAfHeVilK5Mtf8gO6zxQ/edit#heading=h.v6k2o3roarzz].
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