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TaskScheduler.scala
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TaskScheduler.scala
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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
import org.apache.spark.scheduler.SchedulingMode.SchedulingMode
/**
* Low-level task scheduler interface, currently implemented exclusively by TaskSchedulerImpl.
* This interface allows plugging in different task schedulers. Each TaskScheduler schedulers tasks
* for a single SparkContext. These schedulers get sets of tasks submitted to them from the
* DAGScheduler for each stage, and are responsible for sending the tasks to the cluster, running
* them, retrying if there are failures, and mitigating stragglers. They return events to the
* DAGScheduler.
*/
private[spark] trait TaskScheduler {
def rootPool: Pool
def schedulingMode: SchedulingMode
def start(): Unit
// Invoked after system has successfully initialized (typically in spark context).
// Yarn uses this to bootstrap allocation of resources based on preferred locations,
// wait for slave registerations, etc.
def postStartHook() { }
// Disconnect from the cluster.
def stop(): Unit
// Submit a sequence of tasks to run.
def submitTasks(taskSet: TaskSet): Unit
// Cancel a stage.
def cancelTasks(stageId: Int, interruptThread: Boolean)
// Set the DAG scheduler for upcalls. This is guaranteed to be set before submitTasks is called.
def setDAGScheduler(dagScheduler: DAGScheduler): Unit
// Get the default level of parallelism to use in the cluster, as a hint for sizing jobs.
def defaultParallelism(): Int
def waitBackendReady(): Unit = { return }
}