Running Spark job in Oozie using Yarn-cluster

Question

I had created a Spark Job using Oozie which configure run on yarn-cluster. The Spark program is written in Scala and is a very simple program which just initialize SparkContext, println("hello world") and stop the SparkContext.

Below is the workflow.xml:

<workflow-app name="My_Workflow" xmlns="uri:oozie:workflow:0.5">
    <start to="spark-0177"/>
    <kill name="Kill">
        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
    </kill>
    <action name="spark-0177">
        <spark xmlns="uri:oozie:spark-action:0.1">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node>
            <master>yarn-cluster</master>
            <mode>cluster</mode>
            <name>MySpark</name>
              <class>com.test1</class>
            <jar>/user/hue/oozie/workspaces/tl_test/lib/testOozie1.jar</jar>
              <spark-opts>--executor-cores 2  --driver-memory 5g --num-executors 2 --executor-memory 5g</spark-opts>
        </spark>
        <ok to="End"/>
        <error to="Kill"/>
    </action>
    <end name="End"/>
</workflow-app>

However, i was getting the following error:

 Failing Oozie Launcher, Main class [org.apache.oozie.action.hadoop.SparkMain], main() threw exception, Can not create a Path from an empty string
    java.lang.IllegalArgumentException: Can not create a Path from an empty string
        at org.apache.hadoop.fs.Path.checkPathArg(Path.java:127)
        at org.apache.hadoop.fs.Path.<init>(Path.java:135)
        at org.apache.hadoop.fs.Path.<init>(Path.java:94)
        at org.apache.spark.deploy.yarn.Client.copyFileToRemote(Client.scala:191)
        at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$3.apply(Client.scala:254)
        at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$3.apply(Client.scala:248)
        at scala.collection.immutable.List.foreach(List.scala:318)
        at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:248)
        at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:384)
        at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:102)
        at org.apache.spark.deploy.yarn.Client.run(Client.scala:623)
        at org.apache.spark.deploy.yarn.Client$.main(Client.scala:651)
        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:569)
        at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
        at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
        at org.apache.oozie.action.hadoop.SparkMain.runSpark(SparkMain.java:105)
        at org.apache.oozie.action.hadoop.SparkMain.run(SparkMain.java:96)
        at org.apache.oozie.action.hadoop.LauncherMain.run(LauncherMain.java:46)
        at org.apache.oozie.action.hadoop.SparkMain.main(SparkMain.java:40)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:497)
        at org.apache.oozie.action.hadoop.LauncherMapper.map(LauncherMapper.java:228)
        at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
        at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:453)
        at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343)
        at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runSubtask(LocalContainerLauncher.java:370)
        at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runTask(LocalContainerLauncher.java:295)
        at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.access$200(LocalContainerLauncher.java:181)
        at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler$1.run(LocalContainerLauncher.java:224)
        at java.util.concurrent.Executors$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)

    Oozie Launcher failed, finishing Hadoop job gracefully

    Oozie Launcher, uploading action data to HDFS sequence file: hdfs://MYRNDSVRVM350:8020/user/oozie-oozi/0000084-150828094553499-oozie-oozi-W/spark-156b--spark/action-data.seq

    Oozie Launcher ends

Please help as i'm totally stuck already. Thanks.

Answer 1

I meet the exactly same wired problem. It turns out that multiple spaces in <spark-opts> cause this un-informtive error. You have two spaces between --executor-cores 2 --driver-memory 5g.

Answer 2

Can not create a Path from an empty string <- Spark is trying to stage your code, but your Oozie workflow doesn't provide the jar path, hence the empty path exception.

Providing the jar path in Oozie will fix this