[
https://issues.apache.org/jira/browse/BEAM-7848?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Severyn Parkhomenko updated BEAM-7848:
--------------------------------------
Attachment: Selection_042.png
> Add possibility to manage quantity of instances (threads) per worker in
> Python SDK
> ----------------------------------------------------------------------------------
>
> Key: BEAM-7848
> URL: https://issues.apache.org/jira/browse/BEAM-7848
> Project: Beam
> Issue Type: Improvement
> Components: runner-dataflow
> Environment: Python SDK
> ApacheBeam version==2.13.0
> worker_type==n1-standard-4
> Reporter: Severyn Parkhomenko
> Priority: Major
> Attachments: Selection_042.png
>
>
> I'm developing a streaming pipeline with big memory consumption in one of the
> PTransforms.
> After some period after starting this pipeline fails without any specific
> logs.
> !image-2019-07-30-13-28-34-007.png!
> It looks like, that it happens because of OutOfMemory.
> It would be great to set a limit of threads that will be used in a single
> worker to control memory load.
> I found such option in JAVA SDK (--_numberOfWorkerHarnessThreads_), but in
> Python SDK it is absent
--
This message was sent by Atlassian JIRA
(v7.6.14#76016)
