Issue with launching application master

[#1]

Hello Everyone,

Need help while running spark-shell over yarn.

[hadoop@tnn1 ~]$ $SPARK_HOME/bin/spark-shell --master=yarn
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
18/01/03 11:24:52 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/01/03 11:24:58 ERROR spark.SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:85)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:509)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2516)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:918)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:910)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:910)
at org.apache.spark.repl.Main$.createSparkSession(Main.scala:101)
at $line3.$read$$iw$$iw.<init>(<console>:15)
at $line3.$read$$iw.<init>(<console>:42)
at $line3.$read.<init>(<console>:44)
at $line3.$read$.<init>(<console>:48)
at $line3.$read$.<clinit>(<console>)
at $line3.$eval$.$print$lzycompute(<console>:7)
at $line3.$eval$.$print(<console>:6)
at $line3.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)
at scala.tools.nsc.interpreter.IMain$WrappedRequest$$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$1.apply$mcV$sp(SparkILoop.scala:38)
at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214)
at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37)
at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:98)
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$$anonfun$process$1.apply(ILoop.scala:909)
at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
at org.apache.spark.repl.Main$.doMain(Main.scala:74)
at org.apache.spark.repl.Main$.main(Main.scala:54)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:775)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
18/01/03 11:24:58 WARN cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request executors before the AM has registered!
18/01/03 11:24:58 WARN metrics.MetricsSystem: 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:85)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:509)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2516)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:918)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:910)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:910)
at org.apache.spark.repl.Main$.createSparkSession(Main.scala:101)
... 47 elided
<console>:14: error: not found: value spark
import spark.implicits._
^
<console>:14: error: not found: value spark
import spark.sql
^
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.2.1
/_/

Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_151)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

#######################################################################################

#######################################################################################

Below is the log for launched application.

[hadoop@tnn1 ~]$ yarn logs -applicationId application_1514911319329_0002
18/01/03 11:39:34 INFO client.RMProxy: Connecting to ResourceManager at trm1/xx.xx.xxx.x:8032
18/01/03 11:39:34 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable


Container: container_1514911319329_0002_02_000001 on thd1_38079
=================================================================
LogType:stderr
Log Upload Time:Wed Jan 03 11:24:58 +0530 2018
LogLength:87
Log Contents:
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
End of LogType:stderr

LogType:stdout
Log Upload Time:Wed Jan 03 11:24:58 +0530 2018
LogLength:0
Log Contents:
End of LogType:stdout



Container: container_1514911319329_0002_01_000001 on thd2_39094
=================================================================
LogType:stderr
Log Upload Time:Wed Jan 03 11:24:58 +0530 2018
LogLength:87
Log Contents:
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
End of LogType:stderr

LogType:stdout
Log Upload Time:Wed Jan 03 11:24:58 +0530 2018
LogLength:0
Log Contents:
End of LogType:stdout

[hadoop@tnn1 ~]$

Pls suggest the solution.

[#2]

# spark-shell --master yarn Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 18/02/22 15:07:11 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 18/02/22 15:07:12 WARN util.Utils: Service 'SparkUI' could not bind on port 4040. Attempting port 4041. 18/02/22 15:07:12 WARN util.Utils: Service 'SparkUI' could not bind on port 4041. Attempting port 4042. 18/02/22 15:07:12 WARN util.Utils: Service 'SparkUI' could not bind on port 4042. Attempting port 4043. 18/02/22 15:07:12 WARN util.Utils: Service 'SparkUI' could not bind on port 4043. Attempting port 4044. 18/02/22 15:07:13 WARN shortcircuit.DomainSocketFactory: The short-circuit local reads feature cannot be used because libhadoop cannot be loaded. 18/02/22 15:07:15 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME. 18/02/22 15:07:54 ERROR spark.SparkContext: 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:85) at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62) at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173) at org.apache.spark.SparkContext.<init>(SparkContext.scala:509) at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2509) at org.apache.spark.sql.SparkSession$Builder$anonfun$6.apply(SparkSession.scala:909) at org.apache.spark.sql.SparkSession$Builder$anonfun$6.apply(SparkSession.scala:901) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:97) at $line3.$read$iw$iw.<init>(<console>:15) at $line3.$read$iw.<init>(<console>:42) at $line3.$read.<init>(<console>:44) at $line3.$read$.<init>(<console>:48) at $line3.$read$.<clinit>(<console>) at $line3.$eval$.$print$lzycompute(<console>:7) at $line3.$eval$.$print(<console>:6) at $line3.$eval.$print(<console>) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at scala.tools.nsc.interpreter.IMain$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$1.apply$mcV$sp(SparkILoop.scala:38) at org.apache.spark.repl.SparkILoop$anonfun$initializeSpark$1.apply(SparkILoop.scala:37) at org.apache.spark.repl.SparkILoop$anonfun$initializeSpark$1.apply(SparkILoop.scala:37) at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214) at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37) at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:98) at scala.tools.nsc.interpreter.ILoop$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$.doMain(Main.scala:70) at org.apache.spark.repl.Main$.main(Main.scala:53) 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.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$runMain(SparkSubmit.scala:755) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 18/02/22 15:07:54 WARN cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request executors before the AM has registered! 18/02/22 15:07:54 WARN metrics.MetricsSystem: 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:85) at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62) at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173) at org.apache.spark.SparkContext.<init>(SparkContext.scala:509) at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2509) at org.apache.spark.sql.SparkSession$Builder$anonfun$6.apply(SparkSession.scala:909) at org.apache.spark.sql.SparkSession$Builder$anonfun$6.apply(SparkSession.scala:901) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:97) ... 47 elided <console>:14: error: not found: value spark import spark.implicits._ ^ <console>:14: error: not found: value spark import spark.sql ^ Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 2.2.0 /_/ Using Scala version 2.11.8 (OpenJDK 64-Bit Server VM, Java 1.8.0_131) Type in expressions to have them evaluated. Type :help for more information. scala>