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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=352842&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-352842
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ASF GitHub Bot logged work on BEAM-8335:
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Author: ASF GitHub Bot
Created on: 03/Dec/19 18:23
Start Date: 03/Dec/19 18:23
Worklog Time Spent: 10m
Work Description: lukecwik commented on pull request #10107: [BEAM-8335]
Change has_unbounded_sources to predetermined list of sources
URL: https://github.com/apache/beam/pull/10107#discussion_r353346022
##########
File path: sdks/python/apache_beam/runners/interactive/pipeline_instrument.py
##########
@@ -24,13 +24,21 @@
from __future__ import absolute_import
import apache_beam as beam
+from apache_beam.io.gcp.pubsub import ReadFromPubSub
from apache_beam.pipeline import PipelineVisitor
from apache_beam.runners.interactive import cache_manager as cache
from apache_beam.runners.interactive import interactive_environment as ie
READ_CACHE = "_ReadCache_"
WRITE_CACHE = "_WriteCache_"
+# Use a tuple to define the list of unbounded sources. It is not always
feasible
+# to correctly find all the unbounded sources in the SDF world. This is
+# because SDF allows the source to dynamically create sources at runtime.
Review comment:
I'm not sure what you mean here since you can detect which ParDo's contain
splittable dofns as shown here:
https://github.com/apache/beam/blob/2f0061360ccc820fd8865ea63cf3224eb9d47397/sdks/python/apache_beam/transforms/core.py#L1278
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Issue Time Tracking
-------------------
Worklog Id: (was: 352842)
Time Spent: 39h 50m (was: 39h 40m)
> 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: 39h 50m
> 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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