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https://issues.apache.org/jira/browse/BEAM-8457?focusedWorklogId=334265&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-334265
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ASF GitHub Bot logged work on BEAM-8457:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 25/Oct/19 18:14
            Start Date: 25/Oct/19 18:14
    Worklog Time Spent: 10m 
      Work Description: KevinGG commented on pull request #9885: [BEAM-8457] 
Label Dataflow jobs from Notebook
URL: https://github.com/apache/beam/pull/9885
 
 
   1. Changed the pipeline.run() API to allow a runner and an option
   parameter so that a pipeline initially bundled w/ an interactive runner
   can be directly run by other runners from notebook.
   2. Implicitly added the necessary source information through user labels
   when the user does p.run(runner=DataflowRunner(), options=options) or
   DataflowRunner().run_pipeline(p, options).
   3. User '--labels' doesn't support character '.' or '"'. When applying
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 334265)
    Time Spent: 2h 50m  (was: 2h 40m)

> Instrument Dataflow jobs that are launched from Notebooks
> ---------------------------------------------------------
>
>                 Key: BEAM-8457
>                 URL: https://issues.apache.org/jira/browse/BEAM-8457
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-py-interactive
>            Reporter: Ning Kang
>            Assignee: Ning Kang
>            Priority: Major
>             Fix For: 2.17.0
>
>          Time Spent: 2h 50m
>  Remaining Estimate: 0h
>
> Dataflow needs the capability to tell how many Dataflow jobs are launched 
> from the Notebook environment, i.e., the Interactive Runner.
>  # Change the pipeline.run() API to allow supply a runner and an option 
> parameter so that a pipeline initially bundled w/ an interactive runner can 
> be directly run by other runners from notebook.
>  # Implicitly add the necessary source information through user labels when 
> the user does p.run(runner=DataflowRunner()).



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