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https://issues.apache.org/jira/browse/BEAM-5110?focusedWorklogId=132737&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-132737
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ASF GitHub Bot logged work on BEAM-5110:
----------------------------------------
Author: ASF GitHub Bot
Created on: 08/Aug/18 22:57
Start Date: 08/Aug/18 22:57
Worklog Time Spent: 10m
Work Description: angoenka opened a new pull request #6189: [BEAM-5110]
Explicitly count the references for BatchFlinkExecutableStageContext …
URL: https://github.com/apache/beam/pull/6189
…and clean them after TTL
We relied on weak reference and finalize to keep track of active
BatchFlinkExecutableStageContext for each job. This is error prone and sub
optimal.
Introducing explicit reference counting and cleanup of
BatchFlinkExecutableStageContext for each job.
------------------------
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Post-Commit Tests Status (on master branch)
------------------------------------------------------------------------------------------------
Lang | SDK | Apex | Dataflow | Flink | Gearpump | Samza | Spark
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Go | [](https://builds.apache.org/job/beam_PostCommit_Go_GradleBuild/lastCompletedBuild/)
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Java | [](https://builds.apache.org/job/beam_PostCommit_Java_GradleBuild/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Apex_Gradle/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Dataflow_Gradle/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Flink_Gradle/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Gearpump_Gradle/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Samza_Gradle/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Spark_Gradle/lastCompletedBuild/)
Python | [](https://builds.apache.org/job/beam_PostCommit_Python_Verify/lastCompletedBuild/)
| --- | [](https://builds.apache.org/job/beam_PostCommit_Py_VR_Dataflow/lastCompletedBuild/)
</br> [](https://builds.apache.org/job/beam_PostCommit_Py_ValCont/lastCompletedBuild/)
| --- | --- | --- | ---
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Issue Time Tracking
-------------------
Worklog Id: (was: 132737)
Time Spent: 10m
Remaining Estimate: 0h
> Reconile Flink JVM singleton management with deployment
> -------------------------------------------------------
>
> Key: BEAM-5110
> URL: https://issues.apache.org/jira/browse/BEAM-5110
> Project: Beam
> Issue Type: Bug
> Components: runner-flink
> Reporter: Ben Sidhom
> Assignee: Ben Sidhom
> Priority: Major
> Time Spent: 10m
> Remaining Estimate: 0h
>
> [~angoenka] noticed through debugging that multiple instances of
> BatchFlinkExecutableStageContext.BatchFactory are loaded for a given job when
> executing in standalone cluster mode. This context factory is responsible for
> maintaining singleton state across a TaskManager (JVM) in order to share SDK
> Environments across workers in a given job. The multiple-loading breaks
> singleton semantics and results in an indeterminate number of Environments
> being created.
> It turns out that the [Flink classloading
> mechanism|https://ci.apache.org/projects/flink/flink-docs-release-1.5/monitoring/debugging_classloading.html]
> is determined by deployment mode. Note that "user code" as referenced by
> this link is actually the Flink job server jar. Actual end-user code lives
> inside of the SDK Environment and uploaded artifacts.
> In order to maintain singletons without resorting to IPC (for example, using
> file locks and/or additional gRPC servers), we need to force non-dynamic
> classloading. For example, this happens when jobs are submitted to YARN for
> one-off deployments via `flink run`. However, connecting to an existing
> (Flink standalone) deployment results in dynamic classloading.
> We should investigate this behavior and either document (and attempt to
> enforce) deployment modes that are consistent with our requirements, or (if
> possible) create a custom classloader that enforces singleton loading.
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