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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-19785) java.lang.ClassNotFoundException - Scala anonymous function
Date Wed, 01 Mar 2017 13:31:45 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19785?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Sean Owen resolved SPARK-19785.
-------------------------------
    Resolution: Invalid

This should stay on the mailing list 

> java.lang.ClassNotFoundException - Scala anonymous function
> -----------------------------------------------------------
>
>                 Key: SPARK-19785
>                 URL: https://issues.apache.org/jira/browse/SPARK-19785
>             Project: Spark
>          Issue Type: Question
>          Components: Deploy, Spark Core, Spark Submit
>    Affects Versions: 2.1.0
>         Environment: Ubuntu 16.04.1 LTS
>            Reporter: Dominik Safaric
>
> 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. 



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