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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._
import org.apache.hadoop.conf.Configuration
import org.apache.spark.deploy.yarn.YarnAllocationHandler
import org.apache.spark.util.Utils
/**
*
* This scheduler launch worker through Yarn - by call into Client to launch WorkerLauncher as AM.
*/
private[spark] class YarnClientClusterScheduler(sc: SparkContext, conf: Configuration) extends ClusterScheduler(sc) {
def this(sc: SparkContext) = this(sc, new Configuration())
// By default, rack is unknown
override def getRackForHost(hostPort: String): Option[String] = {
val host = Utils.parseHostPort(hostPort)._1
val retval = YarnAllocationHandler.lookupRack(conf, host)
if (retval != null) Some(retval) else None
}
override def postStartHook() {
// The yarn application is running, but the worker might not yet ready
// Wait for a few seconds for the slaves to bootstrap and register with master - best case attempt
Thread.sleep(2000L)
logInfo("YarnClientClusterScheduler.postStartHook done")
}
}
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