What is the --jars you are submitting? You may have conflicting copies of
Spark classes that interfere.
On Wed, Mar 1, 2017, 14:20 Dominik Safaric <dominiksafa...@gmail.com> wrote:
> I've been trying to submit a Spark Streaming application using
> spark-submit to a cluster of mine consisting of a master and two worker
> nodes. The application has been written in Scala, and build using Maven.
> Importantly, the Maven build is configured to produce a fat JAR containing
> all dependencies. Furthermore, the JAR has been distributed to all of
> nodes. The streaming job has been submitted using the following command:
>
> bin/spark-submit --class topology.SimpleProcessingTopology --jars
> /tmp/spark_streaming-1.0-SNAPSHOT.jar --master spark://10.0.0.8:7077
> --verbose /tmp/spark_streaming-1.0-SNAPSHOT.jar
> /tmp/streaming-benchmark.properties
>
> where 10.0.0.8 is the IP address of the master node within the VNET.
>
> However, I keep getting the following exception while starting the
> streaming application:
>
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> Caused by: java.lang.ClassNotFoundException:
> topology.SimpleProcessingTopology$$anonfun$main$1$$anonfun$apply$1
> at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at
> org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
>
> I've checked the content of the JAR using jar tvf and as you can see in
> the output below, it does contain the class in question.
>
> 1735 Wed Mar 01 12:29:20 UTC 2017
> topology/SimpleProcessingTopology$$anonfun$main$1.class
> 702 Wed Mar 01 12:29:20 UTC 2017 topology/SimpleProcessingTopology.class
> 2415 Wed Mar 01 12:29:20 UTC 2017
> topology/SimpleProcessingTopology$$anonfun$main$1$$anonfun$apply$1$$anonfun$apply$2.class
> 2500 Wed Mar 01 12:29:20 UTC 2017
> topology/SimpleProcessingTopology$$anonfun$main$1$$anonfun$apply$1.class
> 7045 Wed Mar 01 12:29:20 UTC 2017 topology/SimpleProcessingTopology$.class
>
> This exception has been caused due to the anonymous function of the
> foreachPartition call:
>
> rdd.foreachPartition(partition => {
> val outTopic = props.getString("application.simple.kafka.out.topic")
> val producer = new KafkaProducer[Array[Byte],Array[Byte]](kafkaParams)
> partition.foreach(record => {
> val producerRecord = new ProducerRecord[Array[Byte],
> Array[Byte]](outTopic, record.key(), record.value())
> producer.send(producerRecord)
> })
> producer.close()
> })
>
> Unfortunately, I am not able to find the root cause of this since so far.
> Hence, I would appreciate if anyone could help me out fixing this issue.
>
>
