Yarn application has already ended! It might have been killed or unable to launch application master

今晚运行spark on yarn 的client模式的时候遇到一个让我很难受的错误
在网上找到了解决的办法，但是问题的具体原因还不是很清楚，希望知道的大牛指点一下，不胜感激！！！

错误如下：

Warning: Master yarn-client is deprecated since 2.0. Please use master "yarn" with specified deploy mode instead.
2019-04-01 19:54:33 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
2019-04-01 19:55:05 WARN  Client:66 - Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
2019-04-01 19:56:15 ERROR SparkContext:91 - Error initializing SparkContext.
org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
	at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:89)
	at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:63)
	at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:164)
	at org.apache.spark.SparkContext.(SparkContext.scala:500)
	at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2493)
	at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:933)
	at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:924)
	at scala.Option.getOrElse(Option.scala:121)
	at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:924)
	at org.apache.spark.repl.Main$.createSparkSession(Main.scala:103)
	at $line3.$read$$iw$$iw.(:15)
	at $line3.$read$$iw.(:43)
	at $line3.$read.(:45)
	at $line3.$read$.(:49)
	at $line3.$read$.()
	at $line3.$eval$.$print$lzycompute(:7)
	at $line3.$eval$.$print(:6)
	at $line3.$eval.$print()
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)
	at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)
	at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638)
	at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637)
	at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)
	at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19)
	at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637)
	at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569)
	at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
	at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)
	at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681)
	at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(SparkILoop.scala:79)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(SparkILoop.scala:79)
	at scala.collection.immutable.List.foreach(List.scala:381)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SparkILoop.scala:79)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply(SparkILoop.scala:79)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply(SparkILoop.scala:79)
	at scala.tools.nsc.interpreter.ILoop.savingReplayStack(ILoop.scala:91)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:78)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:78)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:78)
	at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214)
	at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:77)
	at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:110)
	at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:920)
	at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
	at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
	at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
	at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
	at org.apache.spark.repl.Main$.doMain(Main.scala:76)
	at org.apache.spark.repl.Main$.main(Main.scala:56)
	at org.apache.spark.repl.Main.main(Main.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:894)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
2019-04-01 19:56:16 WARN  YarnSchedulerBackend$YarnSchedulerEndpoint:66 - Attempted to request executors before the AM has registered!
2019-04-01 19:56:16 WARN  MetricsSystem:66 - Stopping a MetricsSystem that is not running
org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
  at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:89)
  at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:63)
  at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:164)
  at org.apache.spark.SparkContext.(SparkContext.scala:500)
  at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2493)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:933)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:924)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:924)
  at org.apache.spark.repl.Main$.createSparkSession(Main.scala:103)
  ... 55 elided

原因貌似因为用java8的原因，在yarn-site.xml配置

    yarn.nodemanager.pmem-check-enabled
    false



    yarn.nodemanager.vmem-check-enabled
    false

原文：https://blog.csdn.net/gg584741/article/details/72825713