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https://issues.apache.org/jira/browse/HADOOP-13128?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiaoyu Yao updated HADOOP-13128:
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Description:
HADOOP-9640 added RPC Fair Call Queue and HADOOP-10597 added RPC backoff to
ensure the fairness usage of the HDFS namenode resources. YARN, the Hadoop
cluster resource manager currently manages the CPU and Memory resources for
jobs/tasks but not the storage resources such as HDFS namenode and datanode
usage directly. As a result of that, a high priority Yarn Job may send too many
RPC requests to HDFS namenode and get demoted into low priority call queues due
to lack of reservation/coordination.
To better support multi-tenancy use cases like above, we propose to manage RPC
server resource usage via coupon mechanism integrated with YARN. The idea is to
allow YARN request HDFS storage resource coupon (e.g., namenode RPC calls,
datanode I/O bandwidth) from namenode on behalf of the job upon submission
time. Once granted, the tasks will include the coupon identifier in RPC header
for the subsequent calls. HDFS namenode RPC scheduler maintains the state of
the coupon usage based on the scheduler policy (fairness or priority) to match
the RPC priority with the YARN scheduling priority.
was:
HADOOP-9640 added RPC Fair Call Queue and HADOOP-10597 added RPC backoff to
ensure the fairness usage of the HDFS namenode resources. YARN, the Hadoop
cluster resource manager currently manages the CPU and Memory resources for
jobs/tasks but not the storage resources such as HDFS namenode and datanode
usage directly. As a result of that, a high priority Yarn Job may send too many
RPC requests to HDFS namenode call queue and get demoted into low priority
namenode call queue due to lack of coordination.
To better support multi-tenancy use cases like above, we propose to manage RPC
server resource usage via coupon mechanism integrated with YARN. The idea is to
allow YARN request HDFS storage resource coupon (e.g., namenode RPC calls,
datanode I/O bandwidth) from namenode on behalf of the job upon submission
time. Once granted, the tasks will include the coupon identifier in RPC header
for the subsequent calls. HDFS namenode RPC scheduler maintains the state of
the coupon usage based on the scheduler policy (fairness or priority) to match
the RPC priority with the YARN scheduling priority.
> Manage Hadoop RPC resource usage via resource coupon
> ----------------------------------------------------
>
> Key: HADOOP-13128
> URL: https://issues.apache.org/jira/browse/HADOOP-13128
> Project: Hadoop Common
> Issue Type: Improvement
> Reporter: Xiaoyu Yao
> Assignee: Xiaoyu Yao
>
> HADOOP-9640 added RPC Fair Call Queue and HADOOP-10597 added RPC backoff to
> ensure the fairness usage of the HDFS namenode resources. YARN, the Hadoop
> cluster resource manager currently manages the CPU and Memory resources for
> jobs/tasks but not the storage resources such as HDFS namenode and datanode
> usage directly. As a result of that, a high priority Yarn Job may send too
> many RPC requests to HDFS namenode and get demoted into low priority call
> queues due to lack of reservation/coordination.
> To better support multi-tenancy use cases like above, we propose to manage
> RPC server resource usage via coupon mechanism integrated with YARN. The idea
> is to allow YARN request HDFS storage resource coupon (e.g., namenode RPC
> calls, datanode I/O bandwidth) from namenode on behalf of the job upon
> submission time. Once granted, the tasks will include the coupon identifier
> in RPC header for the subsequent calls. HDFS namenode RPC scheduler maintains
> the state of the coupon usage based on the scheduler policy (fairness or
> priority) to match the RPC priority with the YARN scheduling priority.
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