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https://issues.apache.org/jira/browse/BEAM-10603?focusedWorklogId=488649&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-488649
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ASF GitHub Bot logged work on BEAM-10603:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 22/Sep/20 23:00
Start Date: 22/Sep/20 23:00
Worklog Time Spent: 10m
Work Description: rohdesamuel commented on a change in pull request
#12800:
URL: https://github.com/apache/beam/pull/12800#discussion_r493079795
##########
File path: sdks/python/apache_beam/runners/interactive/interactive_beam.py
##########
@@ -199,6 +199,93 @@ def display_timezone(self, value):
self._display_timezone = value
+class Recordings():
+ """An introspection interface for recordings for pipelines.
+
+ When a user materializes a PCollection onto disk (eg. ib.show) for a
streaming
+ pipeline, a background recording job is started. This job pulls data from all
+ defined unbounded sources for that PCollection's pipeline. The following
+ methods allow for introspection into that background recording job.
+ """
+ def describe(self, pipeline=None):
+ # type: (Optional[beam.Pipeline]) -> dict[str, Any]
+
+ """Returns a description of all the recordings for the given pipeline.
+
+ If no pipeline is given then this returns a dictionary of descriptions for
+ all pipelines.
+ """
+
+ watching = ie.current_env().watching()
+ description = ie.current_env().describe_all_recordings()
+
+ # In the case that the user has multiple pipelines, this correlates the
+ # pipeline object to the variable name.
Review comment:
This shouldn't be heavily used, but yeah it's pretty inefficient. I
moved this into the InteractiveEnvironment when constructing a RecordingManager
so we only pay the price once per pipeline.
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Issue Time Tracking
-------------------
Worklog Id: (was: 488649)
Time Spent: 41h 10m (was: 41h)
> Large Source Recording for Interarctive Runner
> ----------------------------------------------
>
> Key: BEAM-10603
> URL: https://issues.apache.org/jira/browse/BEAM-10603
> Project: Beam
> Issue Type: Improvement
> Components: runner-py-interactive
> Reporter: Sam Rohde
> Assignee: Sam Rohde
> Priority: P1
> Time Spent: 41h 10m
> Remaining Estimate: 0h
>
> This changes the Interactive Runner to create a long-running background
> caching job that is decoupled from the user pipeline. When a user invokes a
> collect() or show(), it will read from the cache to compute the requested
> PCollections. Previously, the user would have to wait for the cache to be
> fully written to. This allows for the user to start experimenting immediately.
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