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Add YarnClientClusterScheduler and Backend.
With this scheduler, the user application is launched locally, While the executor will be launched by YARN on remote nodes. This enables spark-shell to run upon YARN.
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- core/src/main/scala/org/apache/spark/SparkContext.scala 25 additions, 0 deletionscore/src/main/scala/org/apache/spark/SparkContext.scala
- docs/running-on-yarn.md 25 additions, 2 deletionsdocs/running-on-yarn.md
- yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala 9 additions, 4 deletions.../src/main/scala/org/apache/spark/deploy/yarn/Client.scala
- yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala 23 additions, 17 deletions.../scala/org/apache/spark/deploy/yarn/ClientArguments.scala
- yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerLauncher.scala 246 additions, 0 deletions...n/scala/org/apache/spark/deploy/yarn/WorkerLauncher.scala
- yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientClusterScheduler.scala 47 additions, 0 deletions.../spark/scheduler/cluster/YarnClientClusterScheduler.scala
- yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala 109 additions, 0 deletions.../spark/scheduler/cluster/YarnClientSchedulerBackend.scala
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