I am getting the below error while trying to execute spark submit using oozie on emr - apache-spark

I am running on cluster mode. The apacheds-kerberos-codec-2.0.0-M15.jar is present in multiple places in oozie/share/lib/lib*/spark and oozie/share/lib/lib*/oozie. Is this an environmental issue ?
ava.lang.IllegalArgumentException: Attempt to add (hdfs://ip-172-20-10-53.ec2.internal:8020/user/oozie/share/lib/lib_20170208121307/oozie/apacheds-kerberos-codec-2.0.0-M15.jar) multiple times to the distributed cache.
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11$$anonfun$apply$8.apply(Client.scala:608)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11$$anonfun$apply$8.apply(Client.scala:599)
at scala.collection.mutable.ArraySeq.foreach(ArraySeq.scala:74)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11.apply(Client.scala:599)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11.apply(Client.scala:598)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:598)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:868)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:170)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1154)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1213)
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:738)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
at org.apache.oozie.action.hadoop.SparkMain.runSpark(SparkMain.java:338)
at org.apache.oozie.action.hadoop.SparkMain.run(SparkMain.java:257)
at org.apache.oozie.action.hadoop.LauncherMain.run(LauncherMain.java:60)
at org.apache.oozie.action.hadoop.SparkMain.main(SparkMain.java:78)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.oozie.action.hadoop.LauncherMapper.map(LauncherMapper.java:232)
at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:455)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:344)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runSubtask(LocalContainerLauncher.java:380)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runTask(LocalContainerLauncher.java:301)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.access$200(LocalContainerLauncher.java:187)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler$1.run(LocalContainerLauncher.java:230)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
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)

It appears that the oozie sharelib and the spark sharelib directory share the same jars, and running a spark workflow imports both directories, which hadoop-3 code base doesn't like.
I've had to reorganize the oozie sharelib directory to only have oozie specific jars such that there are no duplicates between both oozie and spark sharelib dirs:
export HADOOP_USER_NAME=oozie
hdfs dfs -mv /user/oozie/share/lib/lib_20170222143042/oozie /user/oozie/share/lib/lib_20170222143042/oozie.old
hdfs dfs -mkdir /user/oozie/share/lib/lib_20170222143042/oozie
hdfs dfs -cp /user/oozie/share/lib/lib_20170222143042/oozie.old/oozie-hadoop-utils-hadoop-2-4.3.0.jar /user/oozie/share/lib/lib_20170222143042/oozie
hdfs dfs -cp /user/oozie/share/lib/lib_20170222143042/oozie.old/oozie-sharelib-oozie-4.3.0.jar /user/oozie/share/lib/lib_20170222143042/oozie
This fixes the immediate issue of being able to run spark workflows from oozie, but I'm not sure if this affects non-spark workflows.

I have an oozie job that starts a spark job, running in Amazon EMR. I got the same error when the EMR Hadoop setup has one instance for the master and one instance for the slaves. When I increased the amount of instances for the slaves to two, everything worked as expected.

Related

Spark job not running when jar is in HDFS

I am trying to run a spark job in standalone mode but the command is not picking up the jar from HDFS.The jar is present in the HDFS location and Its working fine when I run it in local mode.
Below is the command I am using
spark-submit --deploy-mode client --master yarn --class com.main.WordCount /spark/wc.jar
Below is my program:
val conf = new SparkConf().setAppName("WordCount").setMaster("yarn")
val spark = new SparkContext(conf)
val file = spark.textFile(args(0))
val count = file.flatMap(f=>f.split(" ")).map(word=>(word,1)).reduceByKey(_+_).collect
count.foreach(println)
And I am getting below error:
Warning: Local jar /spark/wc.jar does not exist, skipping.
java.lang.ClassNotFoundException: com.main.WordCount
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.util.Utils$.classForName(Utils.scala:228)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:693)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
But If i use deploy mode cluster I am getting below error:
Exception in thread "main" java.io.FileNotFoundException: File file:/spark/wc.jar does not exist
at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:611)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:824)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:601)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:337)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:289)
at org.apache.spark.deploy.yarn.Client.copyFileToRemote(Client.scala:340)
at org.apache.spark.deploy.yarn.Client.org$apache$spark$deploy$yarn$Client$$distribute$1(Client.scala:433)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$10.apply(Client.scala:530)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$10.apply(Client.scala:529)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:529)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:834)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:167)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1119)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1178)
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:736)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Could you please clarify what is local mode. There are only two deploy mode client and cluster, the only difference is in client mode Driver program will run on the system and in cluster mode driver program will run from random node in the cluster.
For spark submit command:
When you execute spark submit command spark will pull all the local resources/files defined with --files , --py-files argument as well as Spark Main Jar to temporary HDFS location/directory, which is created by that particular spark application with the application name. when you give HDFS location, it will fail to location the Jar on local machine. It is mandatory to keep the Jar on local.

Unable to run Spark in yarn-cluster mode

I'm trying to run spark job with YARN in cluster deploy mode.
I tried to run the simpliest spark-submit command only with jar path, class parameter and master yarn-cluster. However I still have the same error, which actually tells me nothing.
Exception in thread "main" org.apache.spark.SparkException: Application application_1506196351647_0032 finished with failed status
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1078)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1125)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.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)
If anyone had the similar problem please let me know, I'm using spark 1.6, hadoop 2.6.

adding multiple jars in Oozie-Spark action

I'm using HDP2.6. where is installed oozie 4.2. and Spark2.
After I tracked Hortonworks guide on this site: https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.6.1/bk_spark-component-guide/content/ch_oozie-spark-action.html for adding libs for Spark2 in 4.2. version of Oozie.
After I submit the job with this add-on:
oozie.action.sharelib.for.spark=spark2
The error I'm getting is this:
2017-07-19 12:36:53,271 WARN SparkActionExecutor:523 - SERVER[] USER[admin] GROUP[-] TOKEN[] APP[Workflow2] JOB[0000012-170717153234639-oozie-oozi-W] ACTION[0000012-170717153234639-oozie-oozi-W#spark_1] Launcher ERROR, reason: Main class [org.apache.oozie.action.hadoop.SparkMain], main() threw exception, Attempt to add (hdfs://:8020/user/oozie/share/lib/lib_20170613110051/oozie/aws-java-sdk-core-1.10.6.jar) multiple times to the distributed cache.
2017-07-19 12:36:53,275 WARN SparkActionExecutor:523 - SERVER[] USER[admin] GROUP[-] TOKEN[] APP[Workflow2] JOB[0000012-170717153234639-oozie-oozi-W] ACTION[0000012-170717153234639-oozie-oozi-W#spark_1] Launcher exception: Attempt to add (hdfs://:8020/user/oozie/share/lib/lib_20170613110051/oozie/aws-java-sdk-core-1.10.6.jar) multiple times to the distributed cache.
java.lang.IllegalArgumentException: Attempt to add (hdfs://:8020/user/oozie/share/lib/lib_20170613110051/oozie/aws-java-sdk-core-1.10.6.jar) multiple times to the distributed cache.
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13$$anonfun$apply$8.apply(Client.scala:629)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13$$anonfun$apply$8.apply(Client.scala:620)
at scala.collection.mutable.ArraySeq.foreach(ArraySeq.scala:74)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13.apply(Client.scala:620)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13.apply(Client.scala:619)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:619)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:892)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:171)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1228)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1287)
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:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:745)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
at org.apache.oozie.action.hadoop.SparkMain.runSpark(SparkMain.java:311)
at org.apache.oozie.action.hadoop.SparkMain.run(SparkMain.java:232)
at org.apache.oozie.action.hadoop.LauncherMain.run(LauncherMain.java:58)
at org.apache.oozie.action.hadoop.SparkMain.main(SparkMain.java:62)
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:497)
at org.apache.oozie.action.hadoop.LauncherMapper.map(LauncherMapper.java:239)
at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:453)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:170)
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:1866)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:164)
I have read that new Spark2 will not work with Spark 2.1 (via oozie anyway) due to a change in how Spark handles multiple files found in distributed cache, as mentioned here: see here
Keep in mind that I'm using Ambari and HDP2.6. How can I deal with this?
You need to check the content of the oozie directory and spark2 directory into the Oozie sharelib. If there are any jars present into both, just remove them from one place and try again. Also, do execute the oozie admin sharelub update command to update it.
Hope this will help you.

running spark on yarn as client

I'm trying to run a spark job with yarn using:
./bin/spark-submit --class "KafkaToMaprfs" --master yarn --deploy-mode client /home/mapr/kafkaToMaprfs/target/scala-2.10/KafkaToMaprfs.jar
But facing this error:
/opt/mapr/hadoop/hadoop-2.7.0 17/01/03 11:19:26 WARN NativeCodeLoader:
Unable to load native-hadoop library for your platform... using
builtin-java classes where applicable 17/01/03 11:19:38 ERROR
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:124)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:64)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
at org.apache.spark.SparkContext.(SparkContext.scala:530)
at KafkaToMaprfs$.main(KafkaToMaprfs.scala:61)
at KafkaToMaprfs.main(KafkaToMaprfs.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:752)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 17/01/03 11:19:39 WARN MetricsSystem: Stopping a MetricsSystem that is
not running Exception in thread "main"
org.apache.spark.SparkException: Yarn application has already ended!
It might have been killed or unable to launch application master.
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:124)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:64)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
at org.apache.spark.SparkContext.(SparkContext.scala:530)
at KafkaToMaprfs$.main(KafkaToMaprfs.scala:61)
at KafkaToMaprfs.main(KafkaToMaprfs.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:752)
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)
I have a multi node cluster, i'm deploying the application from a remote node.
I'm using spark 1.6.1 and hadoop 2.7.x versions.
I didn't set the cluster, so I couldn't find where the mistake lies.
Can anyone please help me fix this?
In my case i'm using MapR distribution.And i didn't configure the environment.
So, when i dug down to the all the conf folders.I made some changes in the below files,
1. In Spark-env.sh,Make sure these values are set right.
export SPARK_LOG_DIR=
export SPARK_PID_DIR=
export HADOOP_HOME=
export HADOOP_CONF_DIR=
export JAVA_HOME=
export SPARK_SUBMIT_OPTIONS=
2. yarn-env.sh.
Make sure the yarn_conf_dir, and java_home are set with correct values.
3. In spark-defaults.conf
1.spark.driver.extraClassPath
2.set value for HADOOP_CONF_DIR
4. HADOOP_CONF_DIR and JAVA_HOME in $SPARK_HOME/conf/spark-env.sh
1.export HADOOP_CONF_DIR=/opt/mapr/hadoop/hadoop-2.7.0/etc/hadoop
2.export JAVA_HOME =
5.spark assembly jar
1.Copy the following JAR file from the local file system to a world-readable location on MapR-FS: Substitute your Spark version and
specific JAR file name in the command.
/opt/mapr/spark/spark-/lib/spark-assembly--hadoop-mapr-.jar
Now i'm able to run my spark application as YARN-CLIENT smoothly using spark-submit.
These are basic essentials to make spark connect with yarn.
Correct me if i missed any other things.

IllegalArgumentException with Spark 1.6

I'm running Spark 1.6.0 on CDH 5.7 and I've upgraded my original application from 1.4.1 to 1.6.0. When I try to run my application (which previously worked fine) I get the following error:
Exception in thread "main" java.lang.IllegalArgumentException: requirement failed
at scala.Predef$.require(Predef.scala:221)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6$$anonfun$apply$3.apply(Client.scala:473)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6$$anonfun$apply$3.apply(Client.scala:471)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6.apply(Client.scala:471)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6.apply(Client.scala:469)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:469)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:725)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:143)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1023)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1083)
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: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)
I submit the application with:
--jars is a comma-separated list of jars (with absolute paths)
--files is a comma-separated list of files (with absolute paths)
--driver-class-path is a colon-separated list of resources (without the full path, just the file names)
I have tried it with full paths for the driver (and executor) class paths, but that gives me the same issue. All files and jars submitted with the app exist, I checked.
Could this be related to the issue with duplicates in the distributed cache or is this another issue?
From the source code I see that the only calls to require without a custom message (as in the stack trace) are related to the distribute() method. If so, how can I run applications without upgrading Spark?
This is the exception which results from having the same path/URI appear twice in the argument to the --files option.

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