Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher - apache-spark

I have this submitted job fine in YARN mode but I get the following error
I added a Spark jar installed locally, but the Spark jar can also be in a world-readable location on HDFS. This allows YARN to cache it on nodes and added .bashrc yarn_config_dir and hadoop_config_dir.
ERROR:
Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
9068548 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO org.apache.spark.deploy.yarn.Client - Application report for application_1531990849146_0010 (state: FAILED)
9068548 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO org.apache.spark.deploy.yarn.Client -
client token: N/A
diagnostics: Application application_1531990849146_0010 failed 2 times due to AM Container for appattempt_1531990849146_0010_000002 exited with exitCode: 1
Failing this attempt.Diagnostics: [2018-07-19 11:56:58.484]Exception from container-launch.
Container id: container_1531990849146_0010_02_000001
Exit code: 1
[2018-07-19 11:56:58.484]
[2018-07-19 11:56:58.486]Container exited with a non-zero exit code 1. Error file: prelaunch.err.
Last 4096 bytes of prelaunch.err :
Last 4096 bytes of stderr :
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
[2018-07-19 11:56:58.486]
[2018-07-19 11:56:58.486]Container exited with a non-zero exit code 1. Error file: prelaunch.err.
Last 4096 bytes of prelaunch.err :
Last 4096 bytes of stderr :
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
[2018-07-19 11:56:58.486]
For more detailed output, check the application tracking page: http://localhost:8088/cluster/app/application_1531990849146_0010 Then click on links to logs of each attempt.
. Failing the application.
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: default
start time: 1532001413903
final status: FAILED
tracking URL: http://localhost:8088/cluster/app/application_1531990849146_0010
user: root
9068611 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO org.apache.spark.deploy.yarn.Client - Deleted staging directory file:/root/.sparkStaging/application_1531990849146_0010
9068612 [bioingine-management-service-akka.actor.default-dispatcher-14] ERROR org.apache.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 com.bioingine.smash.management.services.SmashExtractorService.getSparkSession(SmashExtractorService.scala:79)
at com.bioingine.smash.management.services.SmashExtractorService.getFileHeaders(SmashExtractorService.scala:83)
at com.bioingine.smash.management.services.SmashService$$anonfun$getcolumnHeaders$1.apply(SmashService.scala:90)
at com.bioingine.smash.management.services.SmashService$$anonfun$getcolumnHeaders$1.apply(SmashService.scala:90)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:39)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:415)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
9068618 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO o.s.jetty.server.AbstractConnector - Stopped Spark#2152c728{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
9068619 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO org.apache.spark.ui.SparkUI - Stopped Spark web UI at http://localhost:4040
9068620 [dispatcher-event-loop-16] WARN o.a.s.s.c.YarnSchedulerBackend$YarnSchedulerEndpoint - Attempted to request executors before the AM has registered!
9068621 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO o.a.s.s.c.YarnClientSchedulerBackend - Shutting down all executors
9068621 [dispatcher-event-loop-17] INFO o.a.s.s.c.YarnSchedulerBackend$YarnDriverEndpoint - Asking each executor to shut down
9068622 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO o.a.s.s.c.SchedulerExtensionServices - Stopping SchedulerExtensionServices
(serviceOption=None,
services=List(),
started=false)
9068622 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO o.a.s.s.c.YarnClientSchedulerBackend - Stopped
9068623 [dispatcher-event-loop-20] INFO o.a.s.MapOutputTrackerMasterEndpoint - MapOutputTrackerMasterEndpoint stopped!
9068624 [bioingine-management-service-akka.actor.default-dispatcher-14] ERROR org.apache.spark.util.Utils - Uncaught exception in thread bioingine-management-service-akka.actor.default-dispatcher-14
java.lang.NullPointerException: null
at org.apache.spark.network.shuffle.ExternalShuffleClient.close(ExternalShuffleClient.java:141)
at org.apache.spark.storage.BlockManager.stop(BlockManager.scala:1485)
at org.apache.spark.SparkEnv.stop(SparkEnv.scala:90)
at org.apache.spark.SparkContext$$anonfun$stop$11.apply$mcV$sp(SparkContext.scala:1937)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1317)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1936)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:587)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2509)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:909)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:901)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901)
at com.bioingine.smash.management.services.SmashExtractorService.getSparkSession(SmashExtractorService.scala:79)
at com.bioingine.smash.management.services.SmashExtractorService.getFileHeaders(SmashExtractorService.scala:83)
at com.bioingine.smash.management.services.SmashService$$anonfun$getcolumnHeaders$1.apply(SmashService.scala:90)
at com.bioingine.smash.management.services.SmashService$$anonfun$getcolumnHeaders$1.apply(SmashService.scala:90)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:39)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:415)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
9068624 [bioingine-management-service-akka.actor.default-dispatcher-14] INFO org.apache.spark.SparkContext - Successfully stopped SparkContext
9068627 [bioingine-management-service-akka.actor.default-dispatcher-15] ERROR akka.actor.ActorSystemImpl - Error during processing of request: 'Yarn application has already ended! It might have been killed or unable to launch application master.'. Completing with 500 Internal Server Error response. To change default exception handling behavior, provide a custom ExceptionHandler.
org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:85)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:509)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2509)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:909)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:901)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901)
at com.bioingine.smash.management.services.SmashExtractorService.getSparkSession(SmashExtractorService.scala:79)
at com.bioingine.smash.management.services.SmashExtractorService.getFileHeaders(SmashExtractorService.scala:83)
at com.bioingine.smash.management.services.SmashService$$anonfun$getcolumnHeaders$1.apply(SmashService.scala:90)
at com.bioingine.smash.management.services.SmashService$$anonfun$getcolumnHeaders$1.apply(SmashService.scala:90)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:39)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:415)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
**SparkSession configuration**
new SparkConf().setMaster("yarn").setAppName("Test").set("spark.executor.memory", "3g")
.set("spark.ui.enabled","true")
.set("spark.driver.memory","9g")
.set("spark.default.parallelism","10")
.set("spark.executor.cores","3")
.set("spark.cores.max","9")
.set("spark.memory.offHeap.enabled","true")
.set("spark.memory.offHeap.size","6g")
.set("spark.yarn.am.memory","2g")
.set("spark.yarn.am.cores","2")
.set("spark.yarn.am.cores","2")
.set("spark.yarn.archive","hdfs://localhost:9000/user/spark/share/lib/spark2-hdp-yarn-archive.tar.gz")
.set("spark.yarn.jars","hdfs://localhost:9000/user/spark/share/lib/spark-yarn_2.11.2.2.0.jar")
**We are added below configuration**
1. These entries are in $SPARK_HOME/conf/spark-defaults.conf
spark.driver.extraJavaOptions -Dhdp.version=2.9.0
spark.yarn.am.extraJavaOptions -Dhdp.version=2.9.0
log4j.rootCategory=WARN, console
log4j.appender.console=org.apache.log4j.ConsoleAppender
2. yarn-site.xml
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle,spark_shuffle</value>
<description>shuffle service that needs to be set for Map Reduce to run</description>
</property>
<property>
<name>yarn.nodemanager.aux-services.spark_shuffle.class</name>
<value>org.apache.spark.network.yarn.YarnShuffleService</value>
</property>
<property>
<name>yarn.nodemanager.pmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.application.classpath</name>
<value>/usr/share/hadoop/etc/hadoop,/usr/share/hadoop/,/usr/share/hadoop/lib/,/usr/share/hadoop/share/hadoop/common/,/usr/share/hadoop/share/hadoop/common/lib, /usr/share/hadoop/share/hadoop/hdfs/,/usr/share/hadoop/share/hadoop/hdfs/lib/,/usr/share/hadoop/share/hadoop/mapreduce/,/usr/share/hadoop/share/hadoop/mapreduce/lib/,/usr/share/hadoop/share/hadoop/tools/lib/,/usr/share/hadoop/share/hadoop/yarn/,/usr/share/hadoop/share/hadoop/yarn/lib/*,/usr/share/spark/jars/spark-yarn_2.11-2.2.0.jar</value>
</property>
</configuration>
3.Spark-env.sh
export HADOOP_CONF_DIR=/home/hadoop/hadoop/etc/hadoop
export SPARK_HOME=/home/hadoop/spark
SPARK_DIST_CLASSPATH="/usr/share/spark/jars/*"
4. .bashrc
export JAVA_HOME="/usr/lib/jvm/java-8-openjdk-amd64/"
export SBT_OPTS="-Xms16G -Xmx16G"
export HADOOP_INSTALL=/usr/share/hadoop
export HADOOP_CONF_DIR=/usr/share/hadoop/etc/hadoop/
export YARN_CONF_DIR=/usr/share/hadoop/etc/hadoop/
export HADOOP_MAPRED_HOME=$HADOOP_INSTALL
export HADOOP_COMMON_HOME=$HADOOP_INSTALL
export HADOOP_HDFS_HOME=$HADOOP_INSTALL
export SPARK_CLASSPATH="/usr/share/spark/jars/*"
export SPARK_HOME="/usr/share/spark/"
export PATH=$PATH:$SPARK_HOME

Related

I want to run spark with yarn, but I get a java.net.ConnectException error

I want to run spark on yarn
root#server01:/export/server/spark# bin/spark-shell --master yarn
But it goes to error like this
root#server01:/export/server/spark# bin/spark-shell --master yarn
22/12/06 07:51:42 WARN Utils: Your hostname, server01 resolves to a loopback address: 127.0.1.1; using 192.168.40.133 instead (on interface ens33)
22/12/06 07:51:42 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
22/12/06 07:51:51 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
22/12/06 07:57:58 ERROR YarnClientSchedulerBackend: The YARN application has already ended! It might have been killed or the Application Master may have failed to start. Check the YARN application logs for more details.
22/12/06 07:57:58 ERROR SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: Application application_1670312235175_0001 failed 2 times due to Error launching appattempt_1670312235175_0001_000002. Got exception: java.net.ConnectException: Call From localhost/127.0.0.1 to localhost:41647 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
spark-defaults.conf
spark.eventLog.enabled true
spark.eventLog.dir hdfs://node1:8020/sparklog/
spark.eventLog.compress true
# spark-yarn jar package
spark.yarn.jars hdfs://node1:8020/spark/jars/*
# spark and yarn history server
spark.yarn.historyServer.address node1:18080
yarn-site.xml
<property>
<name>yarn.log.server.url</name>
<value>http://node1:19888/jobhistory/logs</value>
</property>
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>604800</value>
</property>
I verify the spark.yarn.historyServer to node1:19888 and restart spark,but it doesn't work.

spark-submit on local Hadoop-Yarn setup, fails with Stdout path must be absolute error

I have installed the latest Hadoop and Spark versions on my Windows machine.
I am trying to launch one of the provided examples but it fails and I have no idea what the diagnostic means. It seems it's related to the stdout but I can't figure out the root cause.
I launch the following command:
spark-submit --master yarn --class org.apache.spark.examples.JavaSparkPi C:\spark-3.0.1-bin-hadoop3.2\examples\jars\spark-examples_2.12-3.0.1.jar 100
And the exception I have is:
21/01/25 10:53:53 WARN MetricsSystem: Stopping a MetricsSystem that is not running
21/01/25 10:53:53 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
21/01/25 10:53:53 INFO SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: Application application_1611568137841_0002 failed 2 times due to AM Container for appattempt_1611568137841_0002_000002 exited with exitCode: -1
Failing this attempt.Diagnostics:
[2021-01-25 10:53:53.381] Stdout path must be absolute
For more detailed output, check the application tracking page: http://xxxx-PC:8088/cluster/app/application_1611568137841_0002 Then click on links to logs of each attempt.
. Failing the application.
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBack
end.scala:95)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:201)
at org.apache.spark.SparkContext.(SparkContext.scala:555)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2574)
at org.apache.spark.sql.SparkSession$Builder.$anonfun$getOrCreate$2(SparkSession.scala:934)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:928)
at org.apache.spark.examples.JavaSparkPi.main(JavaSparkPi.java:37)
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$$runMain(SparkSubmit.scala:928)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
21/01/25 10:53:53 INFO ShutdownHookManager: Shutdown hook called
21/01/25 10:53:53 INFO ShutdownHookManager: Deleting directory C:\Users\xxx\AppData\Local\Temp\spark-b28ecb32-5e3f-4d6a-973a-c03a7aae0da9
21/01/25 10:53:53 INFO ShutdownHookManager: Deleting directory C:\Users/xxx\AppData\Local\Temp\spark-3665ba77-d2aa-424a-9f75-e772bb5b9104
As for the diagnostics:
Diagnostics:
Application application_1611562870926_0004 failed 2 times due to AM Container for appattempt_1611562870926_0004_000002 exited with exitCode: -1
Failing this attempt.Diagnostics: [2021-01-25 10:29:19.734]Stdout path must be absolute
For more detailed output, check the application tracking page: http://****-PC:8088/cluster/app/application_1611562870926_0004 Then click on links to logs of each attempt.
. Failing the application.
Thank you !
So I am not sure of the root cause yet, it's probably due to the fact that I run under windows and some default property was wrong for Yarn.
When I added the 2 following properties on yarn-site.xml, it worked fine:
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/tmp</value>
</property>
<property>
<name>yarn.log.dir</name>
<value>/tmp</value>
</property>
Hope it helps someone in the future !

Failed to send RPC XXXX in spark-shell Hadoop 3.2.1 and spark 3.0.0

I am trying to run spark shell in psuedodistributed mode on my windows 10 pc having 8 Gigs of ram.
I am able to submit and run a mapreduce wordcount on yarn ,but when i try to initialize a spark shell or spark submit any program with master as yarn it fails with failed to send RPC error.
The error is given below.
Below is my yarn-site.xml config
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>C:\study\hadoop-3.2.1\data\nodemanager</value>
</property>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>127.0.0.1</value>
</property>
<property>
<name>yarn.acl.enable</name>
<value>0</value>
</property>
<property>
<name>yarn.nodemanager.env-whitelist</name>
<value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PERPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_MAPRED_HOME</value>
</property>
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.nodemanager.pmem-check-enabled</name>
<value>false</value>
</property>
<!-- Site specific YARN configuration properties -->
</configuration>
By my initial investigation this seems to be caused by netty io library calling abstractRegion.transfer() method in spark network utils which doesnt seems to be present...
Below is complete error.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/C:/study/hadoop-3.2.1/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/C:/study/hadoop-3.2.1/data/nodemanager/usercache/Administrator/appcache/application_1609008428682_0006/container_1609008428682_0006_01_000001/__spark_libs__/slf4j-log4j12-1.7.30.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]
2020-12-27 01:27:52,370 WARN util.Shell: Did not find winutils.exe: {}
java.io.FileNotFoundException: java.io.FileNotFoundException: HADOOP_HOME and hadoop.home.dir are unset. -see https://wiki.apache.org/hadoop/WindowsProblems
at org.apache.hadoop.util.Shell.fileNotFoundException(Shell.java:548)
at org.apache.hadoop.util.Shell.getHadoopHomeDir(Shell.java:569)
at org.apache.hadoop.util.Shell.getQualifiedBin(Shell.java:592)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:689)
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:78)
at org.apache.hadoop.yarn.conf.YarnConfiguration.<clinit>(YarnConfiguration.java:1159)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:858)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:921)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Caused by: java.io.FileNotFoundException: HADOOP_HOME and hadoop.home.dir are unset.
at org.apache.hadoop.util.Shell.checkHadoopHomeInner(Shell.java:468)
at org.apache.hadoop.util.Shell.checkHadoopHome(Shell.java:439)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:516)
... 5 more
2020-12-27 01:27:52,776 INFO spark.SecurityManager: Changing view acls to: Administrator
2020-12-27 01:27:52,777 INFO spark.SecurityManager: Changing modify acls to: Administrator
2020-12-27 01:27:52,778 INFO spark.SecurityManager: Changing view acls groups to:
2020-12-27 01:27:52,779 INFO spark.SecurityManager: Changing modify acls groups to:
2020-12-27 01:27:52,780 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(Administrator); groups with view permissions: Set(); users with modify permissions: Set(Administrator); groups with modify permissions: Set()
2020-12-27 01:27:53,417 INFO yarn.ApplicationMaster: ApplicationAttemptId: appattempt_1609008428682_0006_000001
2020-12-27 01:27:54,627 INFO client.RMProxy: Connecting to ResourceManager at /127.0.0.1:8030
2020-12-27 01:27:54,727 INFO yarn.YarnRMClient: Registering the ApplicationMaster
2020-12-27 01:27:55,305 INFO client.TransportClientFactory: Successfully created connection to LAPTOP-GQ2OL7O9/192.168.0.106:56588 after 137 ms (0 ms spent in bootstraps)
2020-12-27 01:27:55,341 ERROR client.TransportClient: Failed to send RPC RPC 6402554451456766428 to LAPTOP-GQ2OL7O9/192.168.0.106:56588: io.netty.channel.socket.ChannelOutputShutdownException: Channel output shutdown
io.netty.channel.socket.ChannelOutputShutdownException: Channel output shutdown
at io.netty.channel.AbstractChannel$AbstractUnsafe.shutdownOutput(AbstractChannel.java:587)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:893)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.flush0(AbstractNioChannel.java:313)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush(AbstractChannel.java:847)
at io.netty.channel.DefaultChannelPipeline$HeadContext.flush(DefaultChannelPipeline.java:1264)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.flush(AbstractChannelHandlerContext.java:743)
at io.netty.channel.ChannelOutboundHandlerAdapter.flush(ChannelOutboundHandlerAdapter.java:115)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.flush(AbstractChannelHandlerContext.java:743)
at io.netty.channel.ChannelDuplexHandler.flush(ChannelDuplexHandler.java:117)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.access$1500(AbstractChannelHandlerContext.java:35)
at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)
at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1050)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:464)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoSuchMethodError: org.apache.spark.network.util.AbstractFileRegion.transferred()J
at org.apache.spark.network.util.AbstractFileRegion.transfered(AbstractFileRegion.java:28)
at io.netty.channel.nio.AbstractNioByteChannel.doWrite(AbstractNioByteChannel.java:228)
at io.netty.channel.socket.nio.NioSocketChannel.doWrite(NioSocketChannel.java:282)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:879)
... 21 more
2020-12-27 01:27:55,353 ERROR yarn.ApplicationMaster: Uncaught exception:
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:302)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:101)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:109)
at org.apache.spark.deploy.yarn.ApplicationMaster.runExecutorLauncher(ApplicationMaster.scala:547)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:266)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:890)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:889)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:889)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:921)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Caused by: java.io.IOException: Failed to send RPC RPC 6402554451456766428 to LAPTOP-GQ2OL7O9/192.168.0.106:56588: io.netty.channel.socket.ChannelOutputShutdownException: Channel output shutdown
at org.apache.spark.network.client.TransportClient$RpcChannelListener.handleFailure(TransportClient.java:363)
at org.apache.spark.network.client.TransportClient$StdChannelListener.operationComplete(TransportClient.java:340)
at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)
at io.netty.util.concurrent.DefaultPromise.notifyListeners0(DefaultPromise.java:500)
at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:479)
at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)
at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:122)
at io.netty.util.internal.PromiseNotificationUtil.tryFailure(PromiseNotificationUtil.java:64)
at io.netty.channel.ChannelOutboundBuffer.safeFail(ChannelOutboundBuffer.java:680)
at io.netty.channel.ChannelOutboundBuffer.remove0(ChannelOutboundBuffer.java:294)
at io.netty.channel.ChannelOutboundBuffer.failFlushed(ChannelOutboundBuffer.java:617)
at io.netty.channel.AbstractChannel$AbstractUnsafe.closeOutboundBufferForShutdown(AbstractChannel.java:627)
at io.netty.channel.AbstractChannel$AbstractUnsafe.shutdownOutput(AbstractChannel.java:620)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:893)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.flush0(AbstractNioChannel.java:313)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush(AbstractChannel.java:847)
at io.netty.channel.DefaultChannelPipeline$HeadContext.flush(DefaultChannelPipeline.java:1264)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.flush(AbstractChannelHandlerContext.java:743)
at io.netty.channel.ChannelOutboundHandlerAdapter.flush(ChannelOutboundHandlerAdapter.java:115)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.flush(AbstractChannelHandlerContext.java:743)
at io.netty.channel.ChannelDuplexHandler.flush(ChannelDuplexHandler.java:117)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.access$1500(AbstractChannelHandlerContext.java:35)
at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)
at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1050)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:464)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
at java.lang.Thread.run(Thread.java:748)
Caused by: io.netty.channel.socket.ChannelOutputShutdownException: Channel output shutdown
at io.netty.channel.AbstractChannel$AbstractUnsafe.shutdownOutput(AbstractChannel.java:587)
... 22 more
Caused by: java.lang.NoSuchMethodError: org.apache.spark.network.util.AbstractFileRegion.transferred()J
at org.apache.spark.network.util.AbstractFileRegion.transfered(AbstractFileRegion.java:28)
at io.netty.channel.nio.AbstractNioByteChannel.doWrite(AbstractNioByteChannel.java:228)
at io.netty.channel.socket.nio.NioSocketChannel.doWrite(NioSocketChannel.java:282)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:879)
... 21 more
2020-12-27 01:27:55,357 INFO yarn.ApplicationMaster: Final app status: FAILED, exitCode: 10, (reason: Uncaught exception: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:302)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:101)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:109)
at org.apache.spark.deploy.yarn.ApplicationMaster.runExecutorLauncher(ApplicationMaster.scala:547)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:266)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:890)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:889)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:889)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:921)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Caused by: java.io.IOException: Failed to send RPC RPC 6402554451456766428 to LAPTOP-GQ2OL7O9/192.168.0.106:56588: io.netty.channel.socket.ChannelOutputShutdownException: Channel output shutdown
at org.apache.spark.network.client.TransportClient$RpcChannelListener.handleFailure(TransportClient.java:363)
at org.apache.spark.network.client.TransportClient$StdChannelListener.operationComplete(TransportClient.java:340)
at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)
at io.netty.util.concurrent.DefaultPromise.notifyListeners0(DefaultPromise.java:500)
at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:479)
at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)
at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:122)
at io.netty.util.internal.PromiseNotificationUtil.tryFailure(PromiseNotificationUtil.java:64)
at io.netty.channel.ChannelOutboundBuffer.safeFail(ChannelOutboundBuffer.java:680)
at io.netty.channel.ChannelOutboundBuffer.remove0(ChannelOutboundBuffer.java:294)
at io.netty.channel.ChannelOutboundBuffer.failFlushed(ChannelOutboundBuffer.java:617)
at io.netty.channel.AbstractChannel$AbstractUnsafe.closeOutboundBufferForShutdown(AbstractChannel.java:627)
at io.netty.channel.AbstractChannel$AbstractUnsafe.shutdownOutput(AbstractChannel.java:620)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:893)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.flush0(AbstractNioChannel.java:313)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush(AbstractChannel.java:847)
at io.netty.channel.DefaultChannelPipeline$HeadContext.flush(DefaultChannelPipeline.java:1264)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.flush(AbstractChannelHandlerContext.java:743)
at io.netty.channel.ChannelOutboundHandlerAdapter.flush(ChannelOutboundHandlerAdapter.java:115)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.flush(AbstractChannelHandlerContext.java:743)
at io.netty.channel.ChannelDuplexHandler.flush(ChannelDuplexHandler.java:117)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush0(AbstractChannelHandlerContext.java:770)
at io.netty.channel.AbstractChannelHandlerContext.invokeFlush(AbstractChannelHandlerContext.java:762)
at io.netty.channel.AbstractChannelHandlerContext.access$1500(AbstractChannelHandlerContext.java:35)
at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)
at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1050)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:464)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
at java.lang.Thread.run(Thread.java:748)
Caused by: io.netty.channel.socket.ChannelOutputShutdownException: Channel output shutdown
at io.netty.channel.AbstractChannel$AbstractUnsafe.shutdownOutput(AbstractChannel.java:587)
... 22 more
Caused by: java.lang.NoSuchMethodError: org.apache.spark.network.util.AbstractFileRegion.transferred()J
at org.apache.spark.network.util.AbstractFileRegion.transfered(AbstractFileRegion.java:28)
at io.netty.channel.nio.AbstractNioByteChannel.doWrite(AbstractNioByteChannel.java:228)
at io.netty.channel.socket.nio.NioSocketChannel.doWrite(NioSocketChannel.java:282)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:879)
... 21 more
)
2020-12-27 01:27:55,368 INFO util.ShutdownHookManager: Shutdown hook called
There seems to be no help on internet for my cause...
Thanks in advance.
Caused by: java.lang.NoSuchMethodError: org.apache.spark.network.util.AbstractFileRegion.transferred()J
at org.apache.spark.network.util.AbstractFileRegion.transfered(AbstractFileRegion.java:28)
at io.netty.channel.nio.AbstractNioByteChannel.doWrite(AbstractNioByteChannel.java:228)
at io.netty.channel.socket.nio.NioSocketChannel.doWrite(NioSocketChannel.java:282)
at io.netty.channel.AbstractChannel$AbstractUnsafe.flush0(AbstractChannel.java:879)
... 21 more
This seems like you may have multiple version on the classpath. Ensure you only have one version on the classpath (and this needs to be the right one).

I cant get hive to run jobs with spark

Running hive with spark keeps giving me this error. I have tried many different versions of both hive and spark.
Running hadoop 2.7.3 in standalone mode
it is a diy implementation
right now using spark 2.2 with hive 2.3.5
I tried different versions of hive and spark, I am not sure what exactly the problem is or how to debug this:
0: jdbc:hive2://192.168.71.62:10000> select count(*) from traffic;
Getting log thread is interrupted, since query is done!
Error: org.apache.hive.service.cli.HiveSQLException: Error while processing statement: FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Failed to create spark client.
at org.apache.hive.service.cli.operation.Operation.toSQLException(Operation.java:380)
at org.apache.hive.service.cli.operation.SQLOperation.runQuery(SQLOperation.java:257)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Failed to create spark client.
at org.apache.hadoop.hive.ql.exec.spark.session.SparkSessionImpl.open(SparkSessionImpl.java:64)
at org.apache.hadoop.hive.ql.exec.spark.session.SparkSessionManagerImpl.getSession(SparkSessionManagerImpl.java:115)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1526)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1237)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1232)
at org.apache.hive.service.cli.operation.SQLOperation.runQuery(SQLOperation.java:255)
... 11 more
Caused by: java.lang.RuntimeException: java.util.concurrent.ExecutionException: java.lang.RuntimeException: Cancel client '9be4c047-285d-4578-a934-7bd51294d240'. Error: Child process exited before connecting back with error log Warning: Ignoring non-spark config property: hive.spark.client.server.connect.timeout=90000
Warning: Ignoring non-spark config property: hive.spark.client.rpc.threads=8
Warning: Ignoring non-spark config property: hive.spark.client.connect.timeout=1000
Warning: Ignoring non-spark config property: hive.spark.client.secret.bits=256
Warning: Ignoring non-spark config property: hive.spark.client.rpc.max.size=52428800
19/05/20 12:39:42 WARN util.Utils: Your hostname, suypc183-OptiPlex-3020 resolves to a loopback address: 127.0.0.1; using 192.168.71.62 instead (on interface enp2s0)
19/05/20 12:39:42 WARN util.Utils: Set SPARK_LOCAL_IP if you need to bind to another address
19/05/20 12:39:43 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
19/05/20 12:39:43 INFO yarn.Client: Requesting a new application from cluster with 1 NodeManagers
19/05/20 12:39:43 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container)
19/05/20 12:39:43 INFO yarn.Client: Will allocate AM container, with 1408 MB memory including 384 MB overhead
19/05/20 12:39:43 INFO yarn.Client: Setting up container launch context for our AM
19/05/20 12:39:43 INFO yarn.Client: Setting up the launch environment for our AM container
19/05/20 12:39:43 INFO yarn.Client: Preparing resources for our AM container
19/05/20 12:39:44 INFO yarn.Client: Deleted staging directory hdfs://localhost:9000/user/anonymous/.sparkStaging/application_1558334426394_0004
Exception in thread "main" java.lang.IllegalArgumentException: Can not create a Path from an empty string
at org.apache.hadoop.fs.Path.checkPathArg(Path.java:126)
at org.apache.hadoop.fs.Path.<init>(Path.java:134)
at org.apache.hadoop.fs.Path.<init>(Path.java:93)
at org.apache.spark.deploy.yarn.Client.copyFileToRemote(Client.scala:369)
at org.apache.spark.deploy.yarn.Client.org$apache$spark$deploy$yarn$Client$$distribute$1(Client.scala:490)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:529)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:882)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:171)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1167)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1226)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:744)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:169)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:167)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
at com.google.common.base.Throwables.propagate(Throwables.java:160)
at org.apache.hive.spark.client.SparkClientImpl.<init>(SparkClientImpl.java:125)
at org.apache.hive.spark.client.SparkClientFactory.createClient(SparkClientFactory.java:80)
at org.apache.hadoop.hive.ql.exec.spark.RemoteHiveSparkClient.createRemoteClient(RemoteHiveSparkClient.java:101)
at org.apache.hadoop.hive.ql.exec.spark.RemoteHiveSparkClient.<init>(RemoteHiveSparkClient.java:97)
at org.apache.hadoop.hive.ql.exec.spark.HiveSparkClientFactory.createHiveSparkClient(HiveSparkClientFactory.java:73)
at org.apache.hadoop.hive.ql.exec.spark.session.SparkSessionImpl.open(SparkSessionImpl.java:62)
... 22 more
hive site configs are the following
<property>
<name>hive.exec.scratchdir</name>
<value>/tmp/hive</value>
<description>Scratch space for Hive jobs</description>
</property>
<property>
<name>hive.execution.engine</name>
<value>spark</value>
</property>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>spark.master</name>
<value>yarn</value>
</property>
<property>
<name>spark.executor.memory</name>
<value>2048</value>
</property>
<property>
<name>spark.yarn.archive</name>
<value>hdfs://localhost:8088/user/jars/</value>
</property>
<property>
<name>spark.home</name>
<value>/home/danielphingston/spark</value>
</property>
The most typical problem of connection between Hive and Spark is making sure that Spark knows the HADOOP CONF DIRECTORY. We solve that by provide below statements in the spark-env.sh file within Spark:
HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-$SPARK_CONF_DIR/yarn-conf}
HIVE_CONF_DIR=${HIVE_CONF_DIR:-/etc/hive/conf}
if [ -d "$HIVE_CONF_DIR" ]; then
HADOOP_CONF_DIR="$HADOOP_CONF_DIR:$HIVE_CONF_DIR"
fi
export HADOOP_CONF_DIR
This enables Spark to see where Hadoop directories are present in the file system.

Livy pyspark Python Session Error in Jypyter with Spark Magic - ERROR repl.PythonInterpreter: Process has died with 1

I'm running a spark v2.0.0 YARN cluster. I have livy running beside the Spark master.
I have set up a jupyter Python3 notetebook and have Spark Magic installed and have followed the nessesary instructions to connect Spark Magic to Livy although When I create my session I get an error message from the notebook.
Added endpoint http://spark-master:8998
Starting Spark application
ID YARN Application ID Kind State Spark UI Driver log Current session?
0 None pyspark idle ✔
---------------------------------------------------------------------------
LivyUnexpectedStatusException Traceback (most recent call last)
/opt/conda/lib/python3.5/site-packages/hdijupyterutils/ipywidgetfactory.py in submit_clicked(self, button)
63
64 def submit_clicked(self, button):
---> 65 self.parent_widget.run()
/opt/conda/lib/python3.5/site-packages/sparkmagic/controllerwidget/createsessionwidget.py in run(self)
56
57 try:
---> 58 self.spark_controller.add_session(alias, endpoint, skip, properties)
59 except ValueError as e:
60 self.ipython_display.send_error("""Could not add session with
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/sparkcontroller.py in add_session(self, name, endpoint, skip_if_exists, properties)
79 session = self._livy_session(http_client, properties, self.ipython_display)
80 self.session_manager.add_session(name, session)
---> 81 session.start()
82
83 def get_session_id_for_client(self, name):
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/livysession.py in start(self)
148 else:
149 command = Command("sqlContext")
--> 150 (success, out) = command.execute(self)
151 if success:
152 self.ipython_display.writeln(u"SparkContext available as 'sc'.")
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/command.py in execute(self, session)
29 statement_id = -1
30 try:
---> 31 session.wait_for_idle()
32 data = {u"code": self.code}
33 response = session.http_client.post_statement(session.id, data)
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/livysession.py in wait_for_idle(self, seconds_to_wait)
238 .format(self.id, self.status)
239 self.logger.error(error)
--> 240 raise LivyUnexpectedStatusException(u'{} See logs:\n{}'.format(error, self.get_logs()))
241
242 if seconds_to_wait <= 0.0:
LivyUnexpectedStatusException: Session 0 unexpectedly reached final status 'error'. See logs:
Error I get from the Livy logs when creating a new session in the manage spark section of jupyter
17/02/10 13:06:08 INFO StateStore$: Using BlackholeStateStore for recovery.
17/02/10 13:06:08 INFO BatchSessionManager: Recovered 0 batch sessions. Next session id: 0
17/02/10 13:06:08 INFO InteractiveSessionManager: Recovered 0 interactive sessions. Next session id: 0
17/02/10 13:06:08 INFO InteractiveSessionManager: Heartbeat watchdog thread started.
17/02/10 13:06:08 INFO WebServer: Starting server on http://spark-master:8998
17/02/10 13:06:34 INFO InteractiveSession$: Creating LivyClient for sessionId: 0
17/02/10 13:06:34 WARN RSCConf: Your hostname, spark-master, resolves to a loopback address, but we couldn't find any external IP address!
17/02/10 13:06:34 WARN RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
17/02/10 13:06:35 INFO InteractiveSessionManager: Registering new session 0
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 INFO driver.RSCDriver: Starting RPC server...
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 WARN rsc.RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 INFO driver.RSCDriver: Received job request 3ca8a52b-8dd5-41f0-8151-a8201d72d422
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 INFO driver.RSCDriver: SparkContext not yet up, queueing job request.
17/02/10 13:06:36 INFO ContextLauncher: Setting default log level to "WARN".
17/02/10 13:06:36 INFO ContextLauncher: To adjust logging level use sc.setLogLevel(newLevel).
17/02/10 13:06:36 INFO ContextLauncher: 17/02/10 13:06:36 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/02/10 13:06:37 INFO ContextLauncher: 17/02/10 13:06:37 ERROR repl.PythonInterpreter: Process has died with 1
17/02/10 13:06:37 INFO RSCClient: Received result for 3ca8a52b-8dd5-41f0-8151-a8201d72d422
and get this output in the livy logs
I'm unable to put my finger on what the exact issue/fix is. I'm able to create a successful connection if I set my session to use the Scala language instead of the Python. Although I only get the error if I set the session language to python. If someone knows a solution to connecting a livy-repl pyspark session in Jupyter please let me know!
UPDATE
Livy still fails to create a PySpark session.
curl -v -X POST --data '{"kind": "pyspark"}' -H "Content-Type: application/json" example.com/sessions
The session state will go straight from "starting" to "failed". YARN logs on Resource Manager give the following right before the livy session fails.
To adjust logging level use sc.setLogLevel(newLevel).
17/02/26 05:02:25 WARN rsc.RSCConf: Your hostname, yarn-slave1, resolves to a loopback address, but we couldn't find any external IP address!
17/02/26 05:02:25 WARN rsc.RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
17/02/26 05:02:32 ERROR repl.PythonInterpreter: Process has died with 1
17/02/26 05:02:33 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000002 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000002
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:33 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
17/02/26 05:02:40 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000005 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000005
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:40 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
17/02/26 05:02:47 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000006 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000006
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:47 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
17/02/26 05:02:53 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000007 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000007
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:53 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
spark-defaults.conf
spark.yarn.appMasterEnv.PYSPARK_PYTHON python2
core-site.xml
<property>
<name>hadoop.proxyuser.livy.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.livy.hosts</name>
<value>*</value>
</property>
livy.conf
livy.server.host = 0.0.0.0
livy.server.port = 8998
livy.spark.master = yarn
livy.spark.deployMode = cluster
I was able to reproduce this issue.
The problem seems to be that spark 2.0.0 and livy have incompatible pyspark versions. If you update spark to the most recent version(currently 2.1.0) the pyspark versions can communicate and the spark session is created without a hitch.
I had faced similar issue even with spark 2.1.1 and livy. Livy-session status went to "error" from "starting". Turned out that I was using Java-7 while Livy and Spark need Java-8. Solved my issue.
I was facing a similar issue. Turns out the culprit was livy version. When replaced cloudera livy with apache livy-0.6.0-incubating version, the problem was solved; and I was able to create pyspark kind session on livy.

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