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https://issues.apache.org/jira/browse/YARN-1404?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13844772#comment-13844772
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Vinod Kumar Vavilapalli commented on YARN-1404:
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Re Tucu's reply
bq. Regarding ACLs and an on/off switch: IMO they are not necessary for the
following reason. You need an external system installed and running in the node
to use the resources of an unmanaged container. If you have direct access into
the node to start the external system, you are 'trusted'. If you don't have
direct access you cannot use the resources of an unmanaged container.
Unfortunately that is not enough. We are exposing an API on NodeManager that
anybody can use. The ACL prevents that.
bq. In the case of managed containers we don't have a liveliness 'report' and
the container process could very well be hung. In such scenario is the
responsibility of the AM to detected the liveliness of the container process
and react if it is considered hung.
Like I said, we do have an implicit liveliness report - process liveliness. And
NodeManager depends on that today to inform the app of container-finishes.
bq. Regarding NM assume a whole lot of things about containers 3 bullet items:
For the my current use case none if this is needed. It could be relatively easy
to enable such functionality if a use case that needs it arises.
So, then we start off with the assumption that they are not needed? That
creates two very different code paths for managed and unmanded containers. If
possible we should avoid that.
> Enable external systems/frameworks to share resources with Hadoop leveraging
> Yarn resource scheduling
> -----------------------------------------------------------------------------------------------------
>
> Key: YARN-1404
> URL: https://issues.apache.org/jira/browse/YARN-1404
> Project: Hadoop YARN
> Issue Type: New Feature
> Components: nodemanager
> Affects Versions: 2.2.0
> Reporter: Alejandro Abdelnur
> Assignee: Alejandro Abdelnur
> Attachments: YARN-1404.patch
>
>
> Currently Hadoop Yarn expects to manage the lifecycle of the processes its
> applications run workload in. External frameworks/systems could benefit from
> sharing resources with other Yarn applications while running their workload
> within long-running processes owned by the external framework (in other
> words, running their workload outside of the context of a Yarn container
> process).
> Because Yarn provides robust and scalable resource management, it is
> desirable for some external systems to leverage the resource governance
> capabilities of Yarn (queues, capacities, scheduling, access control) while
> supplying their own resource enforcement.
> Impala is an example of such system. Impala uses Llama
> (http://cloudera.github.io/llama/) to request resources from Yarn.
> Impala runs an impalad process in every node of the cluster, when a user
> submits a query, the processing is broken into 'query fragments' which are
> run in multiple impalad processes leveraging data locality (similar to
> Map-Reduce Mappers processing a collocated HDFS block of input data).
> The execution of a 'query fragment' requires an amount of CPU and memory in
> the impalad. As the impalad shares the host with other services (HDFS
> DataNode, Yarn NodeManager, Hbase Region Server) and Yarn Applications
> (MapReduce tasks).
> To ensure cluster utilization that follow the Yarn scheduler policies and it
> does not overload the cluster nodes, before running a 'query fragment' in a
> node, Impala requests the required amount of CPU and memory from Yarn. Once
> the requested CPU and memory has been allocated, Impala starts running the
> 'query fragment' taking care that the 'query fragment' does not use more
> resources than the ones that have been allocated. Memory is book kept per
> 'query fragment' and the threads used for the processing of the 'query
> fragment' are placed under a cgroup to contain CPU utilization.
> Today, for all resources that have been asked to Yarn RM, a (container)
> process must be started via the corresponding NodeManager. Failing to do
> this, will result on the cancelation of the container allocation
> relinquishing the acquired resource capacity back to the pool of available
> resources. To avoid this, Impala starts a dummy container process doing
> 'sleep 10y'.
> Using a dummy container process has its drawbacks:
> * the dummy container process is in a cgroup with a given number of CPU
> shares that are not used and Impala is re-issuing those CPU shares to another
> cgroup for the thread running the 'query fragment'. The cgroup CPU
> enforcement works correctly because of the CPU controller implementation (but
> the formal specified behavior is actually undefined).
> * Impala may ask for CPU and memory independent of each other. Some requests
> may be only memory with no CPU or viceversa. Because a container requires a
> process, complete absence of memory or CPU is not possible even if the dummy
> process is 'sleep', a minimal amount of memory and CPU is required for the
> dummy process.
> Because of this it is desirable to be able to have a container without a
> backing process.
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