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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.hadoop.yarn.api.records.{ApplicationId, YarnApplicationState}
import org.apache.spark.{SparkException, Logging, SparkContext}
import org.apache.spark.deploy.yarn.{Client, ClientArguments, YarnSparkHadoopUtil}
import org.apache.spark.scheduler.TaskSchedulerImpl
import scala.collection.mutable.ArrayBuffer
private[spark] class YarnClientSchedulerBackend(
scheduler: TaskSchedulerImpl,
sc: SparkContext)
extends CoarseGrainedSchedulerBackend(scheduler, sc.env.actorSystem)
with Logging {
if (conf.getOption("spark.scheduler.minRegisteredResourcesRatio").isEmpty) {
minRegisteredRatio = 0.8
}
var client: Client = null
var appId: ApplicationId = null
var checkerThread: Thread = null
var stopping: Boolean = false
var totalExpectedExecutors = 0
private[spark] def addArg(optionName: String, envVar: String, sysProp: String,
arrayBuf: ArrayBuffer[String]) {
if (System.getenv(envVar) != null) {
arrayBuf += (optionName, System.getenv(envVar))
} else if (sc.getConf.contains(sysProp)) {
arrayBuf += (optionName, sc.getConf.get(sysProp))
}
}
override def start() {
super.start()
val driverHost = conf.get("spark.driver.host")
val driverPort = conf.get("spark.driver.port")
val hostport = driverHost + ":" + driverPort
sc.ui.foreach { ui => conf.set("spark.driver.appUIAddress", ui.appUIHostPort) }
val argsArrayBuf = new ArrayBuffer[String]()
argsArrayBuf += (
"--args", hostport
)
// process any optional arguments, given either as environment variables
// or system properties. use the defaults already defined in ClientArguments
// if things aren't specified. system properties override environment
// variables.
List(("--driver-memory", "SPARK_MASTER_MEMORY", "spark.master.memory"),
("--driver-memory", "SPARK_DRIVER_MEMORY", "spark.driver.memory"),
("--num-executors", "SPARK_WORKER_INSTANCES", "spark.executor.instances"),
("--num-executors", "SPARK_EXECUTOR_INSTANCES", "spark.executor.instances"),
("--executor-memory", "SPARK_WORKER_MEMORY", "spark.executor.memory"),
("--executor-memory", "SPARK_EXECUTOR_MEMORY", "spark.executor.memory"),
("--executor-cores", "SPARK_WORKER_CORES", "spark.executor.cores"),
("--executor-cores", "SPARK_EXECUTOR_CORES", "spark.executor.cores"),
("--queue", "SPARK_YARN_QUEUE", "spark.yarn.queue"),
("--name", "SPARK_YARN_APP_NAME", "spark.app.name"))
.foreach { case (optName, envVar, sysProp) => addArg(optName, envVar, sysProp, argsArrayBuf) }
logDebug("ClientArguments called with: " + argsArrayBuf)
val args = new ClientArguments(argsArrayBuf.toArray, conf)
totalExpectedExecutors = args.numExecutors
client = new Client(args, conf)
appId = client.runApp()
waitForApp()
checkerThread = yarnApplicationStateCheckerThread()
}
def waitForApp() {
// TODO : need a better way to find out whether the executors are ready or not
// maybe by resource usage report?
while(true) {
val report = client.getApplicationReport(appId)
logInfo("Application report from ASM: \n" +
"\t appMasterRpcPort: " + report.getRpcPort() + "\n" +
"\t appStartTime: " + report.getStartTime() + "\n" +
"\t yarnAppState: " + report.getYarnApplicationState() + "\n"
)
// Ready to go, or already gone.
val state = report.getYarnApplicationState()
if (state == YarnApplicationState.RUNNING) {
return
} else if (state == YarnApplicationState.FINISHED ||
state == YarnApplicationState.FAILED ||
state == YarnApplicationState.KILLED) {
throw new SparkException("Yarn application already ended," +
"might be killed or not able to launch application master.")
}
Thread.sleep(1000)
}
}
private def yarnApplicationStateCheckerThread(): Thread = {
val t = new Thread {
override def run() {
while (!stopping) {
val report = client.getApplicationReport(appId)
val state = report.getYarnApplicationState()
if (state == YarnApplicationState.FINISHED || state == YarnApplicationState.KILLED
|| state == YarnApplicationState.FAILED) {
logError(s"Yarn application already ended: $state")
sc.stop()
stopping = true
}
Thread.sleep(1000L)
}
checkerThread = null
Thread.currentThread().interrupt()
}
}
t.setName("Yarn Application State Checker")
t.setDaemon(true)
t.start()
t
}
override def stop() {
stopping = true
super.stop()
client.stop
logInfo("Stopped")
}
override def sufficientResourcesRegistered(): Boolean = {
totalRegisteredExecutors.get() >= totalExpectedExecutors * minRegisteredRatio
}
override def applicationId(): Option[String] = Option(appId).map(_.toString())
}
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