Hi, My version of Spark is 1.0.2. I am trying to use Spark-cassandra-connector to execute an update csql statement inside an CassandraConnector(conf).withSessionDo block :
CassandraConnector(conf).withSessionDo { session => { myRdd.foreach { case (ip, values) => session.execute( {An csql update statement}) } } } The above code is in the main method of the driver object. When I run the above code (in local mode), I get an exception : java.io.NotSerializableException: com.datastax.spark.connector.cql.SessionProxy Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: com.datastax.spark.connector.cql.SessionProxy at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1049) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1033) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1031) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1031) at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:772) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$16$$anonfun$apply$1.apply$mcVI$sp(DAGScheduler.scala:906) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$16$$anonfun$apply$1.apply(DAGScheduler.scala:903) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$16$$anonfun$apply$1.apply(DAGScheduler.scala:903) Is there a way to use an RDD inside an CassandraConnector(conf).withSessionDo block ? Thanks in advance for any assistance ! Shing --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org