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https://issues.apache.org/jira/browse/BEAM-6778?focusedWorklogId=213312&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-213312
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ASF GitHub Bot logged work on BEAM-6778:
----------------------------------------
Author: ASF GitHub Bot
Created on: 14/Mar/19 18:07
Start Date: 14/Mar/19 18:07
Worklog Time Spent: 10m
Work Description: boyuanzz commented on pull request #7937: [BEAM-6778]
Enable Bundle Finalization in Python SDK harness over FnApi
URL: https://github.com/apache/beam/pull/7937#discussion_r265700768
##########
File path: sdks/python/apache_beam/runners/worker/sdk_worker.py
##########
@@ -186,11 +186,11 @@ def task():
try:
self._execute(lambda: worker.do_instruction(work), work)
finally:
- # Delete the instruction_id <-> worker mapping
- self._instruction_id_vs_worker.pop(work.instruction_id, None)
- # Put the worker back in the free worker pool
- self.workers.put(worker)
-
+ if not worker.has_active_processors():
Review comment:
If looking at here:
https://github.com/apache/beam/blob/05bc3f6b8d46dbbdd6a17b19db01b92fc9c9e276/sdks/python/apache_beam/runners/worker/sdk_worker.py#L212,
the SdkHarness is still caching the ```instruction_id -> worker``` map. With
BundleProcessorCache, I think this map can be removed and when there is a new
request coming in, get a new worker directly. wdyt?
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Issue Time Tracking
-------------------
Worklog Id: (was: 213312)
Time Spent: 3h 20m (was: 3h 10m)
> Enable Bundle Finalization in Python SDK
> ----------------------------------------
>
> Key: BEAM-6778
> URL: https://issues.apache.org/jira/browse/BEAM-6778
> Project: Beam
> Issue Type: New Feature
> Components: sdk-py-harness
> Reporter: Boyuan Zhang
> Assignee: Boyuan Zhang
> Priority: Major
> Time Spent: 3h 20m
> Remaining Estimate: 0h
>
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