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https://issues.apache.org/jira/browse/BEAM-8151?focusedWorklogId=342837&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-342837
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ASF GitHub Bot logged work on BEAM-8151:
----------------------------------------
Author: ASF GitHub Bot
Created on: 13/Nov/19 19:46
Start Date: 13/Nov/19 19:46
Worklog Time Spent: 10m
Work Description: acrites commented on pull request #10091: (WIP)
[BEAM-8151] Swap to create SdkWorkers on demand when processing portable jobs
URL: https://github.com/apache/beam/pull/10091#discussion_r345964729
##########
File path: sdks/python/apache_beam/runners/worker/sdk_worker.py
##########
@@ -269,6 +250,24 @@ def _monitor_process_bundle(self):
logging.warning('Unable to schedule instruction %s for %s',
instruction_id, scheduling_delay)
+ def _get_or_create_worker(self):
+ """Gets an idle worker or creates a new one if none are idle."""
+ try:
+ self.workers.get(wait=False)
+ except queue.Empty:
Review comment:
We're now creating a new worker any time we need work and the queue is
empty. When we return the worker after processing, do we have a limit to the
number allowed in the queue? If not, then the queue size will always grow to
the high water mark of number needed.
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Issue Time Tracking
-------------------
Worklog Id: (was: 342837)
Time Spent: 9h 50m (was: 9h 40m)
> Allow the Python SDK to use many many threads
> ---------------------------------------------
>
> Key: BEAM-8151
> URL: https://issues.apache.org/jira/browse/BEAM-8151
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core, sdk-py-harness
> Reporter: Luke Cwik
> Assignee: Luke Cwik
> Priority: Major
> Time Spent: 9h 50m
> Remaining Estimate: 0h
>
> We need to use a thread pool which shrinks the number of active threads when
> they are not being used.
>
> This is to prevent any stuckness issues related to a runner scheduling more
> work items then there are "work" threads inside the SDK harness.
>
> By default the control plane should have all "requests" being processed in
> parallel and the runner is responsible for not overloading the SDK with too
> much work.
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