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https://issues.apache.org/jira/browse/YARN-4844?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wangda Tan updated YARN-4844:
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Description:
We use int32 for memory now, if a cluster has 10k nodes, each node has 210G
memory, we will get a negative total cluster memory.
And another case that easier overflows int32 is: we added all pending resources
of running apps to cluster's total pending resources. If a problematic app
requires too much resources (let's say 1M+ containers, each of them has 3G
containers), int32 will be not enough.
Even if we can cap each app's pending request, we cannot handle the case that
there're many running apps, each of them has capped but still significant
numbers of pending resources.
So we may possibly need to add getMemoryLong/getVirtualCoreLong to
was:
We use int32 for memory now, if a cluster has 10k nodes, each node has 210G
memory, we will get a negative total cluster memory.
And another case that easier overflows int32 is: we added all pending resources
of running apps to cluster's total pending resources. If a problematic app
requires too much resources (let's say 1M+ containers, each of them has 3G
containers), int32 will be not enough.
Even if we can cap each app's pending request, we cannot handle the case that
there're many running apps, each of them has capped but still significant
numbers of pending resources.
So we may possibly need to upgrade int32 memory field (could include v-cores as
well) to int64 to avoid integer overflow.
> Add getMemoryLong/getVirtualCoreLong to o.a.h.y.api.records.Resource
> --------------------------------------------------------------------
>
> Key: YARN-4844
> URL: https://issues.apache.org/jira/browse/YARN-4844
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: api
> Reporter: Wangda Tan
> Assignee: Wangda Tan
> Priority: Blocker
> Attachments: YARN-4844.1.patch, YARN-4844.2.patch, YARN-4844.3.patch
>
>
> We use int32 for memory now, if a cluster has 10k nodes, each node has 210G
> memory, we will get a negative total cluster memory.
> And another case that easier overflows int32 is: we added all pending
> resources of running apps to cluster's total pending resources. If a
> problematic app requires too much resources (let's say 1M+ containers, each
> of them has 3G containers), int32 will be not enough.
> Even if we can cap each app's pending request, we cannot handle the case that
> there're many running apps, each of them has capped but still significant
> numbers of pending resources.
> So we may possibly need to add getMemoryLong/getVirtualCoreLong to
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