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org.apache.spark.scheduler.cluster.SchedulerBackend.scala Maven / Gradle / Ivy

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.scheduler.cluster

import org.apache.spark.SparkContext

/**
 * 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.
 */
private[spark] trait SchedulerBackend {
  def start(): Unit
  def stop(): Unit
  def reviveOffers(): Unit
  def defaultParallelism(): Int

  def killTask(taskId: Long, executorId: String): Unit = throw new UnsupportedOperationException

  // Memory used by each executor (in megabytes)
  protected val executorMemory: Int = SparkContext.executorMemoryRequested
}




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