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https://issues.apache.org/jira/browse/BEAM-7926?focusedWorklogId=330670&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-330670
]
ASF GitHub Bot logged work on BEAM-7926:
----------------------------------------
Author: ASF GitHub Bot
Created on: 18/Oct/19 17:25
Start Date: 18/Oct/19 17:25
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #9741: [BEAM-7926]
Visualize PCollection
URL: https://github.com/apache/beam/pull/9741#discussion_r336592169
##########
File path:
sdks/python/apache_beam/runners/interactive/interactive_environment.py
##########
@@ -105,3 +113,33 @@ def set_cache_manager(self, cache_manager):
def cache_manager(self):
"""Gets the cache manager held by current Interactive Environment."""
return self._cache_manager
+
+ def set_pipeline_result(self, pipeline, result):
Review comment:
It's not used yet. It should be invoked by the InteractiveRunner once we
have all the building blocks ready.
What we are planning to do is to only allow one job for one user pipeline
running at the same time within a runner instance.
So if the user re-executes p.run() for an async running job. The runner
should cancel the running job using current tracked pipeline_result and start a
new one, then track the new pipeline_result.
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Issue Time Tracking
-------------------
Worklog Id: (was: 330670)
Time Spent: 5h 40m (was: 5.5h)
> Visualize PCollection with Interactive Beam
> -------------------------------------------
>
> 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: 5h 40m
> Remaining Estimate: 0h
>
> Support auto plotting / charting of materialized data of a given PCollection
> with Interactive Beam.
> Say an Interactive Beam pipeline defined as
> p = create_pipeline()
> pcoll = p | 'Transform' >> transform()
> The use can call a single function and get auto-magical charting of the data
> as materialized pcoll.
> e.g., visualize(pcoll)
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