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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 spark.scheduler
import spark.scheduler.cluster.TaskInfo
import scala.collection.mutable.Map
import spark.TaskEndReason
import spark.executor.TaskMetrics
/**
* Interface for getting events back from the TaskScheduler.
*/
private[spark] trait TaskSchedulerListener {
// A task has started.
def taskStarted(task: Task[_], taskInfo: TaskInfo)
// A task has finished or failed.
def taskEnded(task: Task[_], reason: TaskEndReason, result: Any, accumUpdates: Map[Long, Any],
taskInfo: TaskInfo, taskMetrics: TaskMetrics): Unit
// A node was added to the cluster.
def executorGained(execId: String, hostPort: String): Unit
// A node was lost from the cluster.
def executorLost(execId: String): Unit
// The TaskScheduler wants to abort an entire task set.
def taskSetFailed(taskSet: TaskSet, reason: String): Unit
}
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