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package spark.scheduler.cluster
/**
* A backend interface for cluster scheduling systems that allows plugging in different ones under
* ClusterScheduler. We assume a Mesos-like model where the application gets resource offers as
* machines become available and can launch tasks on them.
*/
trait SchedulerBackend {
def start(): Unit
def stop(): Unit
def reviveOffers(): Unit
def defaultParallelism(): Int
// TODO: Probably want to add a killTask too
}
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