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+/*
+ * 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, Utils}
+
+/**
+ * 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
+
+ // Memory used by each executor (in megabytes)
+ protected val executorMemory: Int = SparkContext.executorMemoryRequested
+
+ // TODO: Probably want to add a killTask too
+}