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https://issues.apache.org/jira/browse/BEAM-7348?focusedWorklogId=245359&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-245359
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ASF GitHub Bot logged work on BEAM-7348:
----------------------------------------
Author: ASF GitHub Bot
Created on: 20/May/19 17:30
Start Date: 20/May/19 17:30
Worklog Time Spent: 10m
Work Description: angoenka commented on pull request #8599: [BEAM-7348]
Support environment expiration
URL: https://github.com/apache/beam/pull/8599#discussion_r285310082
##########
File path:
sdks/java/core/src/main/java/org/apache/beam/sdk/options/PortablePipelineOptions.java
##########
@@ -80,4 +80,10 @@
int getEnvironmentCacheMillis();
void setEnvironmentCacheMillis(int environmentCacheMillis);
+
+ @Description("Duration in milliseconds for environment expiration. 0 means
no expiration.")
+ @Default.Integer(0)
+ int getEnvironmentExpirationMillis();
Review comment:
Instead of time, shall we use bundle count for cleanup as I think memory
leak is more closely related to bundle count?
However, I don't know how users will guess the right value.
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Issue Time Tracking
-------------------
Worklog Id: (was: 245359)
Time Spent: 1h (was: 50m)
> Option to expire SDK worker environments
> ----------------------------------------
>
> Key: BEAM-7348
> URL: https://issues.apache.org/jira/browse/BEAM-7348
> Project: Beam
> Issue Type: Improvement
> Components: runner-core
> Affects Versions: 2.12.0
> Reporter: Thomas Weise
> Assignee: Thomas Weise
> Priority: Major
> Labels: portability, portability-flink
> Time Spent: 1h
> Remaining Estimate: 0h
>
> We discovered that Python SDK workers are susceptible to memory leaks that
> are quite hard to identify and/or fix. This becomes an issue in streaming
> pipelines, where the workers run "forever". It would be good if the user has
> an option to recycle the workers when there is no other practical way to
> address (slow) resource leaks.
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