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https://issues.apache.org/jira/browse/BEAM-10308?focusedWorklogId=450042&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-450042
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ASF GitHub Bot logged work on BEAM-10308:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 23/Jun/20 22:02
Start Date: 23/Jun/20 22:02
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on pull request #12067:
URL: https://github.com/apache/beam/pull/12067#issuecomment-648451338
One shortcoming of this approach is that component ids are stored in a
_global_ cache. I think it would be better if the cache could be scoped to a
pipeline, but that would be more difficult to implement. I don't _think_ the
global cache would cause any issues except for an extreme case where thousands
of pipelines are being launched from a single python process and we consume a
huge amount of memory.
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Issue Time Tracking
-------------------
Worklog Id: (was: 450042)
Time Spent: 20m (was: 10m)
> Component id assignement is not consistent across PipelineContext instances
> ---------------------------------------------------------------------------
>
> Key: BEAM-10308
> URL: https://issues.apache.org/jira/browse/BEAM-10308
> Project: Beam
> Issue Type: Bug
> Components: cross-language, sdk-py-core
> Reporter: Brian Hulette
> Assignee: Brian Hulette
> Priority: P1
> Time Spent: 20m
> Remaining Estimate: 0h
>
> The "unique ref" ids used in PipelineContext are generated on the fly, which
> can cause us to get a different id for the same component in different
> contexts.
> This becomes a problem when ExternalTransform is used, because it creates its
> own pipeline context for expansion. So its possible the component ids in the
> expansion request will actually refer to an entirely different component when
> the pipeline is finally assembled for execution.
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