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https://issues.apache.org/jira/browse/YARN-8569?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16639178#comment-16639178
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Eric Yang commented on YARN-8569:
---------------------------------
[~suma.shivaprasad] Thanks for the review, appinfo.json is probably better
choice than AMInfo.json because the API can be used by code other than
Application master even though it might be rare. Info in appinfo.json provides
no additional information to the file name. How about app.json in short for
easy nomenclature of naming this file? Good catch on the file close, will
update in the next patch.
> Create an interface to provide cluster information to application
> -----------------------------------------------------------------
>
> Key: YARN-8569
> URL: https://issues.apache.org/jira/browse/YARN-8569
> Project: Hadoop YARN
> Issue Type: Sub-task
> Reporter: Eric Yang
> Assignee: Eric Yang
> Priority: Major
> Labels: Docker
> Attachments: YARN-8569 YARN sysfs interface to provide cluster
> information to application.pdf, YARN-8569.001.patch, YARN-8569.002.patch,
> YARN-8569.003.patch, YARN-8569.004.patch, YARN-8569.005.patch,
> YARN-8569.006.patch, YARN-8569.007.patch, YARN-8569.008.patch
>
>
> Some program requires container hostnames to be known for application to run.
> For example, distributed tensorflow requires launch_command that looks like:
> {code}
> # On ps0.example.com:
> $ python trainer.py \
> --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 \
> --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 \
> --job_name=ps --task_index=0
> # On ps1.example.com:
> $ python trainer.py \
> --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 \
> --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 \
> --job_name=ps --task_index=1
> # On worker0.example.com:
> $ python trainer.py \
> --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 \
> --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 \
> --job_name=worker --task_index=0
> # On worker1.example.com:
> $ python trainer.py \
> --ps_hosts=ps0.example.com:2222,ps1.example.com:2222 \
> --worker_hosts=worker0.example.com:2222,worker1.example.com:2222 \
> --job_name=worker --task_index=1
> {code}
> This is a bit cumbersome to orchestrate via Distributed Shell, or YARN
> services launch_command. In addition, the dynamic parameters do not work
> with YARN flex command. This is the classic pain point for application
> developer attempt to automate system environment settings as parameter to end
> user application.
> It would be great if YARN Docker integration can provide a simple option to
> expose hostnames of the yarn service via a mounted file. The file content
> gets updated when flex command is performed. This allows application
> developer to consume system environment settings via a standard interface.
> It is like /proc/devices for Linux, but for Hadoop. This may involve
> updating a file in distributed cache, and allow mounting of the file via
> container-executor.
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