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如何在客户端模式下使用YARN运行spark-shell？

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我在15节点的Hadoop集群上安装了 spark-1.6.1-bin-hadoop2.6.tgz . 所有节点都运行 Java 1.8.0_72 和最新版本的Hadoop . Hadoop集群本身是功能性的，例如YARN可以成功运行各种MapReduce作业 .

我可以在节点上本地运行Spark Shell，而不会出现以下命令的任何问题： $SPARK_HOME/bin/spark-shell .

我也可以成功运行一些Spark示例，例如使用YARN和集群模式的SparkPi .

但是当我尝试使用部署模式 client 在YARN上运行Spark Shell时，我遇到了问题：

hadoopu@hadoop2:~$ $SPARK_HOME/bin/spark-shell --master yarn --deploy-mode client
16/03/21 15:15:20 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
...
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.6.1
      /_/

Using Scala version 2.10.5 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_72)
Type in expressions to have them evaluated.
Type :help for more information.
...
16/03/21 15:15:24 INFO MemoryStore: MemoryStore started with capacity 511.1 MB
16/03/21 15:15:24 INFO SparkEnv: Registering OutputCommitCoordinator
16/03/21 15:15:24 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/03/21 15:15:24 INFO SparkUI: Started SparkUI at http://10.108.57.32:4040
16/03/21 15:15:24 INFO RMProxy: Connecting to ResourceManager at hadoop2/10.108.57.32:8032
16/03/21 15:15:24 INFO Client: Requesting a new application from cluster with 13 NodeManagers
16/03/21 15:15:25 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (131072 MB per container)
16/03/21 15:15:25 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
16/03/21 15:15:25 INFO Client: Setting up container launch context for our AM
16/03/21 15:15:25 INFO Client: Setting up the launch environment for our AM container
16/03/21 15:15:25 INFO Client: Preparing resources for our AM container
16/03/21 15:15:25 WARN DomainSocketFactory: The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
16/03/21 15:15:25 INFO Client: Uploading resource file:/opt/spark-1.6.1-bin-hadoop2.6/lib/spark-assembly-1.6.1-hadoop2.6.0.jar -> hdfs://hadoop1:9000/user/hadoopu/.sparkStaging/application_1458568053208_0006/spark-assembly-1.6.1-hadoop2.6.0.jar
16/03/21 15:15:28 INFO Client: Uploading resource file:/tmp/spark-c9077c60-b379-439e-aeb4-85948df70df5/__spark_conf__7479505398141092205.zip -> hdfs://hadoop1:9000/user/hadoopu/.sparkStaging/application_1458568053208_0006/__spark_conf__7479505398141092205.zip
16/03/21 15:15:28 INFO SecurityManager: Changing view acls to: hadoopu
16/03/21 15:15:28 INFO SecurityManager: Changing modify acls to: hadoopu
16/03/21 15:15:28 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoopu); users with modify permissions: Set(hadoopu)
16/03/21 15:15:28 INFO Client: Submitting application 6 to ResourceManager
16/03/21 15:15:28 INFO YarnClientImpl: Submitted application application_1458568053208_0006
16/03/21 15:15:29 INFO Client: Application report for application_1458568053208_0006 (state: ACCEPTED)
16/03/21 15:15:29 INFO Client:
     client token: N/A
     diagnostics: AM container is launched, waiting for AM container to Register with RM
     ApplicationMaster host: N/A
     ApplicationMaster RPC port: -1
     queue: default
     start time: 1458569728506
     final status: UNDEFINED
     tracking URL: http://hadoop2:8088/proxy/application_1458568053208_0006/
     user: hadoopu
16/03/21 15:15:30 INFO Client: Application report for application_1458568053208_0006 (state: ACCEPTED)
16/03/21 15:15:31 INFO Client: Application report for application_1458568053208_0006 (state: ACCEPTED)
16/03/21 15:15:32 INFO YarnSchedulerBackend$YarnSchedulerEndpoint: ApplicationMaster registered as NettyRpcEndpointRef(null)
16/03/21 15:15:32 INFO YarnClientSchedulerBackend: Add WebUI Filter. org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter, Map(PROXY_HOSTS -> hadoop2, PROXY_URI_BASES -> http://hadoop2:8088/proxy/application_1458568053208_0006), /proxy/application_1458568053208_0006
16/03/21 15:15:32 INFO JettyUtils: Adding filter: org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter
16/03/21 15:15:32 INFO Client: Application report for application_1458568053208_0006 (state: RUNNING)
16/03/21 15:15:32 INFO Client:
     client token: N/A
     diagnostics: N/A
     ApplicationMaster host: 10.108.57.41
     ApplicationMaster RPC port: 0
     queue: default
     start time: 1458569728506
     final status: UNDEFINED
     tracking URL: http://hadoop2:8088/proxy/application_1458568053208_0006/
     user: hadoopu
16/03/21 15:15:32 INFO YarnClientSchedulerBackend: Application application_1458568053208_0006 has started running.
16/03/21 15:15:32 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 50170.
16/03/21 15:15:32 INFO NettyBlockTransferService: Server created on 50170
16/03/21 15:15:32 INFO BlockManagerMaster: Trying to register BlockManager
16/03/21 15:15:32 INFO BlockManagerMasterEndpoint: Registering block manager 10.108.57.32:50170 with 511.1 MB RAM, BlockManagerId(driver, 10.108.57.32, 50170)
16/03/21 15:15:32 INFO BlockManagerMaster: Registered BlockManager
16/03/21 15:15:37 INFO YarnSchedulerBackend$YarnSchedulerEndpoint: ApplicationMaster registered as NettyRpcEndpointRef(null)
16/03/21 15:15:37 INFO YarnClientSchedulerBackend: Add WebUI Filter. org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter, Map(PROXY_HOSTS -> hadoop2, PROXY_URI_BASES -> http://hadoop2:8088/proxy/application_1458568053208_0006), /proxy/application_1458568053208_0006
16/03/21 15:15:37 INFO JettyUtils: Adding filter: org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter
16/03/21 15:15:39 ERROR YarnClientSchedulerBackend: Yarn application has already exited with state FINISHED!
16/03/21 15:15:39 INFO SparkUI: Stopped Spark web UI at http://10.108.57.32:4040
16/03/21 15:15:39 INFO YarnClientSchedulerBackend: Shutting down all executors
16/03/21 15:15:39 INFO YarnClientSchedulerBackend: Asking each executor to shut down
16/03/21 15:15:39 INFO YarnClientSchedulerBackend: Stopped
16/03/21 15:15:39 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
16/03/21 15:15:39 INFO MemoryStore: MemoryStore cleared
16/03/21 15:15:39 INFO BlockManager: BlockManager stopped
16/03/21 15:15:39 INFO BlockManagerMaster: BlockManagerMaster stopped
16/03/21 15:15:39 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
16/03/21 15:15:39 INFO SparkContext: Successfully stopped SparkContext
16/03/21 15:15:39 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
16/03/21 15:15:39 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
16/03/21 15:15:39 INFO RemoteActorRefProvider$RemotingTerminator: Remoting shut down.
16/03/21 15:15:54 INFO YarnClientSchedulerBackend: SchedulerBackend is ready for scheduling beginning after waiting maxRegisteredResourcesWaitingTime: 30000(ms)
16/03/21 15:15:54 ERROR SparkContext: Error initializing SparkContext.
java.lang.NullPointerException
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:584)
    at org.apache.spark.repl.SparkILoop.createSparkContext(SparkILoop.scala:1017)
    at $line3.$read$$iwC$$iwC.<init>(<console>:15)
    at $line3.$read$$iwC.<init>(<console>:24)
    at $line3.$read.<init>(<console>:26)
    at $line3.$read$.<init>(<console>:30)
    at $line3.$read$.<clinit>(<console>)
    at $line3.$eval$.<init>(<console>:7)
    at $line3.$eval$.<clinit>(<console>)
    at $line3.$eval.$print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
    at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
    at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
    at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
    at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
    at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
    at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:125)
    at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
    at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
    at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
    at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
    at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
    at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:108)
    at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
    at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
    at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
    at org.apache.spark.repl.Main$.main(Main.scala:31)
    at org.apache.spark.repl.Main.main(Main.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
16/03/21 15:15:54 INFO SparkContext: SparkContext already stopped.
java.lang.NullPointerException
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:584)
    at org.apache.spark.repl.SparkILoop.createSparkContext(SparkILoop.scala:1017)
    at $iwC$$iwC.<init>(<console>:15)
    at $iwC.<init>(<console>:24)
    at <init>(<console>:26)
    at .<init>(<console>:30)
    at .<clinit>(<console>)
    at .<init>(<console>:7)
    at .<clinit>(<console>)
    at $print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
    at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
    at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
    at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
    at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
    at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
    at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:125)
    at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
    at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
    at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
    at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
    at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
    at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:108)
    at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
    at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
    at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
    at org.apache.spark.repl.Main$.main(Main.scala:31)
    at org.apache.spark.repl.Main.main(Main.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

java.lang.NullPointerException
    at org.apache.spark.sql.SQLContext$.createListenerAndUI(SQLContext.scala:1367)
    at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:101)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at org.apache.spark.repl.SparkILoop.createSQLContext(SparkILoop.scala:1028)
    at $iwC$$iwC.<init>(<console>:15)
    at $iwC.<init>(<console>:24)
    at <init>(<console>:26)
    at .<init>(<console>:30)
    at .<clinit>(<console>)
    at .<init>(<console>:7)
    at .<clinit>(<console>)
    at $print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
    at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
    at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
    at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
    at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
    at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
    at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:132)
    at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
    at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
    at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
    at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
    at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
    at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:108)
    at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
    at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
    at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
    at org.apache.spark.repl.Main$.main(Main.scala:31)
    at org.apache.spark.repl.Main.main(Main.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

<console>:16: error: not found: value sqlContext
         import sqlContext.implicits._
                ^
<console>:16: error: not found: value sqlContext
         import sqlContext.sql
                ^

scala>

scala> sc
<console>:20: error: not found: value sc
              sc
              ^

scala>

我've also went to the YARN Web UI, found the Spark Shell in the list of FINISHED applications, then clicked on the application to see the logs. I'已找到两个带有 stderr 日志的节点：

SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/mnt/ssd1/tmp/nm-local-dir/usercache/hadoopu/filecache/13/spark-assembly-1.6.1-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/hadoop-3.0.0-SNAPSHOT/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
16/03/21 15:07:20 INFO ApplicationMaster: Registered signal handlers for [TERM, HUP, INT]
16/03/21 15:07:21 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/03/21 15:07:21 INFO ApplicationMaster: ApplicationAttemptId: appattempt_1458568053208_0005_000002
16/03/21 15:07:22 WARN DomainSocketFactory: The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
16/03/21 15:07:22 INFO SecurityManager: Changing view acls to: hadoopu
16/03/21 15:07:22 INFO SecurityManager: Changing modify acls to: hadoopu
16/03/21 15:07:22 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoopu); users with modify permissions: Set(hadoopu)
16/03/21 15:07:22 INFO ApplicationMaster: Waiting for Spark driver to be reachable.
16/03/21 15:07:22 INFO ApplicationMaster: Driver now available: 10.108.57.32:39824
16/03/21 15:07:22 INFO ApplicationMaster$AMEndpoint: Add WebUI Filter. AddWebUIFilter(org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter,Map(PROXY_HOSTS -> hadoop2, PROXY_URI_BASES -> http://hadoop2:8088/proxy/application_1458568053208_0005),/proxy/application_1458568053208_0005)
16/03/21 15:07:22 INFO RMProxy: Connecting to ResourceManager at hadoop2/10.108.57.32:8030
16/03/21 15:07:22 INFO YarnRMClient: Registering the ApplicationMaster
16/03/21 15:07:22 INFO YarnAllocator: Will request 2 executor containers, each with 1 cores and 1408 MB memory including 384 MB overhead
16/03/21 15:07:22 INFO YarnAllocator: Container request (host: Any, capability: <memory:1408, vCores:1>)
16/03/21 15:07:22 INFO YarnAllocator: Container request (host: Any, capability: <memory:1408, vCores:1>)
16/03/21 15:07:22 INFO ApplicationMaster: Started progress reporter thread with (heartbeat : 3000, initial allocation : 200) intervals
16/03/21 15:07:23 INFO AMRMClientImpl: Received new token for : hadoop14:32420
16/03/21 15:07:23 INFO AMRMClientImpl: Received new token for : hadoop3:35904
16/03/21 15:07:23 INFO YarnAllocator: Launching container container_1458568053208_0005_02_000002 for on host hadoop14
16/03/21 15:07:23 INFO YarnAllocator: Launching ExecutorRunnable. driverUrl: spark://CoarseGrainedScheduler@10.108.57.32:39824,  executorHostname: hadoop14
16/03/21 15:07:23 INFO YarnAllocator: Launching container container_1458568053208_0005_02_000003 for on host hadoop3
16/03/21 15:07:23 INFO ExecutorRunnable: Starting Executor Container
16/03/21 15:07:23 INFO YarnAllocator: Launching ExecutorRunnable. driverUrl: spark://CoarseGrainedScheduler@10.108.57.32:39824,  executorHostname: hadoop3
16/03/21 15:07:23 INFO ExecutorRunnable: Starting Executor Container
16/03/21 15:07:23 INFO YarnAllocator: Received 2 containers from YARN, launching executors on 2 of them.
16/03/21 15:07:23 INFO ContainerManagementProtocolProxy: yarn.client.max-cached-nodemanagers-proxies : 0
16/03/21 15:07:23 INFO ContainerManagementProtocolProxy: yarn.client.max-cached-nodemanagers-proxies : 0
16/03/21 15:07:23 INFO ExecutorRunnable: Setting up ContainerLaunchContext
16/03/21 15:07:23 INFO ExecutorRunnable: Setting up ContainerLaunchContext
16/03/21 15:07:23 INFO ExecutorRunnable: Preparing Local resources
16/03/21 15:07:23 INFO ExecutorRunnable: Preparing Local resources
16/03/21 15:07:23 INFO ExecutorRunnable: Prepared Local resources Map(__spark__.jar -> resource { scheme: "hdfs" host: "hadoop1" port: 9000 file: "/user/hadoopu/.sparkStaging/application_1458568053208_0005/spark-assembly-1.6.1-hadoop2.6.0.jar" } size: 187698038 timestamp: 1458569230874 type: FILE visibility: PRIVATE)
16/03/21 15:07:23 INFO ExecutorRunnable: Prepared Local resources Map(__spark__.jar -> resource { scheme: "hdfs" host: "hadoop1" port: 9000 file: "/user/hadoopu/.sparkStaging/application_1458568053208_0005/spark-assembly-1.6.1-hadoop2.6.0.jar" } size: 187698038 timestamp: 1458569230874 type: FILE visibility: PRIVATE)
16/03/21 15:07:23 INFO ExecutorRunnable: 
===============================================================================
YARN executor launch context:
  env:
    CLASSPATH -> {{PWD}}<CPS>{{PWD}}/__spark__.jar<CPS>$HADOOP_CONF_DIR<CPS>$HADOOP_COMMON_HOME/share/hadoop/common/*<CPS>$HADOOP_COMMON_HOME/share/hadoop/common/lib/*<CPS>$HADOOP_HDFS_HOME/share/hadoop/hdfs/*<CPS>$HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/*<CPS>$HADOOP_YARN_HOME/share/hadoop/yarn/*<CPS>$HADOOP_YARN_HOME/share/hadoop/yarn/lib/*<CPS>$HADOOP_PREFIX/share/hadoop/tools/lib/*<CPS>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*<CPS>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*
    SPARK_LOG_URL_STDERR -> http://hadoop3:8042/node/containerlogs/container_1458568053208_0005_02_000003/hadoopu/stderr?start=-4096
    SPARK_YARN_STAGING_DIR -> .sparkStaging/application_1458568053208_0005
    SPARK_YARN_CACHE_FILES_FILE_SIZES -> 187698038
    SPARK_USER -> hadoopu
    SPARK_YARN_CACHE_FILES_VISIBILITIES -> PRIVATE
    SPARK_YARN_MODE -> true
    SPARK_YARN_CACHE_FILES_TIME_STAMPS -> 1458569230874
    SPARK_LOG_URL_STDOUT -> http://hadoop3:8042/node/containerlogs/container_1458568053208_0005_02_000003/hadoopu/stdout?start=-4096
    SPARK_YARN_CACHE_FILES -> hdfs://hadoop1:9000/user/hadoopu/.sparkStaging/application_1458568053208_0005/spark-assembly-1.6.1-hadoop2.6.0.jar#__spark__.jar

  command:
    {{JAVA_HOME}}/bin/java -server -XX:OnOutOfMemoryError='kill %p' -Xms1024m -Xmx1024m -Djava.io.tmpdir={{PWD}}/tmp '-Dspark.driver.port=39824' -Dspark.yarn.app.container.log.dir=<LOG_DIR> org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url spark://CoarseGrainedScheduler@10.108.57.32:39824 --executor-id 2 --hostname hadoop3 --cores 1 --app-id application_1458568053208_0005 --user-class-path file:$PWD/__app__.jar 1> <LOG_DIR>/stdout 2> <LOG_DIR>/stderr
===============================================================================

16/03/21 15:07:23 INFO ExecutorRunnable: 
===============================================================================
YARN executor launch context:
  env:
    CLASSPATH -> {{PWD}}<CPS>{{PWD}}/__spark__.jar<CPS>$HADOOP_CONF_DIR<CPS>$HADOOP_COMMON_HOME/share/hadoop/common/*<CPS>$HADOOP_COMMON_HOME/share/hadoop/common/lib/*<CPS>$HADOOP_HDFS_HOME/share/hadoop/hdfs/*<CPS>$HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/*<CPS>$HADOOP_YARN_HOME/share/hadoop/yarn/*<CPS>$HADOOP_YARN_HOME/share/hadoop/yarn/lib/*<CPS>$HADOOP_PREFIX/share/hadoop/tools/lib/*<CPS>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*<CPS>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*
    SPARK_LOG_URL_STDERR -> http://hadoop14:8042/node/containerlogs/container_1458568053208_0005_02_000002/hadoopu/stderr?start=-4096
    SPARK_YARN_STAGING_DIR -> .sparkStaging/application_1458568053208_0005
    SPARK_YARN_CACHE_FILES_FILE_SIZES -> 187698038
    SPARK_USER -> hadoopu
    SPARK_YARN_CACHE_FILES_VISIBILITIES -> PRIVATE
    SPARK_YARN_MODE -> true
    SPARK_YARN_CACHE_FILES_TIME_STAMPS -> 1458569230874
    SPARK_LOG_URL_STDOUT -> http://hadoop14:8042/node/containerlogs/container_1458568053208_0005_02_000002/hadoopu/stdout?start=-4096
    SPARK_YARN_CACHE_FILES -> hdfs://hadoop1:9000/user/hadoopu/.sparkStaging/application_1458568053208_0005/spark-assembly-1.6.1-hadoop2.6.0.jar#__spark__.jar

  command:
    {{JAVA_HOME}}/bin/java -server -XX:OnOutOfMemoryError='kill %p' -Xms1024m -Xmx1024m -Djava.io.tmpdir={{PWD}}/tmp '-Dspark.driver.port=39824' -Dspark.yarn.app.container.log.dir=<LOG_DIR> org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url spark://CoarseGrainedScheduler@10.108.57.32:39824 --executor-id 1 --hostname hadoop14 --cores 1 --app-id application_1458568053208_0005 --user-class-path file:$PWD/__app__.jar 1> <LOG_DIR>/stdout 2> <LOG_DIR>/stderr
===============================================================================
...
16/03/21 15:07:25 ERROR ApplicationMaster: RECEIVED SIGNAL 15: SIGTERM
16/03/21 15:07:25 INFO ApplicationMaster: Final app status: UNDEFINED, exitCode: 0, (reason: Shutdown hook called before final status was reported.)
16/03/21 15:07:25 INFO ApplicationMaster: Unregistering ApplicationMaster with UNDEFINED (diag message: Shutdown hook called before final status was reported.)
16/03/21 15:07:25 INFO AMRMClientImpl: Waiting for application to be successfully unregistered.
16/03/21 15:07:25 INFO ApplicationMaster: Deleting staging directory .sparkStaging/application_1458568053208_0005
16/03/21 15:07:25 INFO ShutdownHookManager: Shutdown hook called

任何想法为什么我不能在客户端模式下运行YARN上的Spark Shell？

hadoop apache-spark yarn

1 回答

  • 0

    我遇到过同样的问题 . 事实证明，我的登录节点和群集之间是防火墙：群集正在尝试连接到被阻止的随机端口上的登录节点 . 删除防火墙规则，或将shell移动到群集中没有任何阻止访问的防火墙规则的节点之一 .

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