Spark java.lang.NullPointerException when using tuples

I am using the GraphX API for spark to build a graph and process it with Pregel API. The error does not happen if I return an argument tuple from vprog function, but if I return a new tuple using the same tuple, I get null point error. Here is the relevant code:

val verticesRDD = cleanDtaDF.select("ChildHash", "DN").rdd.map(row => (row(0).toString.toLong, (row(1).toString.toDouble,row(0).toString.toLong)))

val edgesRDD = (rawDtaDF.select("ChildHash", "ParentHash", "dealer_code", "dealer_customer_number", "parent_dealer_cust_number").rdd
        .map(row => Edge(row.get(0).toString.toLong, row.get(1).toString.toLong, (row(3) + " is a child of " + row(4), " when dealer is " + row.get(2)))))

val myGraph = Graph(verticesRDD, edgesRDD)

def vprog(vertexId: VertexId, vertexDTA:(Double, Long), msg: Double): (Double, Long) = {
        (vertexDTA._1, vertexDTA._2)
}
val result = myGraph.pregel(0.0, 1, activeDirection = EdgeDirection.Out)(vprog,t => Iterator((t.dstId, t.srcAttr._2)),(x, y) => x + y)

The error does not happen if I make a simple change to vprog(...)--not access the tuples' members:

def vprog(vertexId: VertexId, vertexDTA:(Double, Long), msg: Double): (Double, Long) = {
        vertexDTA
}

The error is

[Stage 101:>              (0 + 0) / 200][Stage 102:>              (0 + 4) / 200]18/03/10 20:43:16 WARN scheduler.TaskSetManager: Lost task 1.0 in stage 102.0 (TID 5959, ue1lslaved25.na.aws.cat.com, executor 146): java.lang.NullPointerException
        at $line69.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.vprog(<console>:60)
        at $line70.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$2.apply(<console>:75)
        at $line70.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$2.apply(<console>:75)
        at org.apache.spark.graphx.Pregel$$anonfun$1.apply(Pregel.scala:125)
        at org.apache.spark.graphx.Pregel$$anonfun$1.apply(Pregel.scala:125)
        at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
        at org.apache.spark.graphx.impl.GraphImpl$$anonfun$5.apply(GraphImpl.scala:129)
        at org.apache.spark.graphx.impl.GraphImpl$$anonfun$5.apply(GraphImpl.scala:129)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
        at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:216)
        at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:988)
        at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:979)
        at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:919)
        at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:979)
        at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:697)
        at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
        at org.apache.spark.scheduler.Task.run(Task.scala:99)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)

Solution

This issue has a simple explanation. It's not related with Spark or Graphx.

Having the function (just strip out irrelevant items from the original):

def vprog(vertexDTA:(Double, Long)): (Double, Long) = {
   (vertexDTA._1, vertexDTA._2)
}

If the arg vertexDTA is null, both vertexDTA._1 and vertexDTA._2 will throw NullPointerException.

If we change the function to

def vprog(vertexDTA:(Double, Long)): (Double, Long) = {
   vertexDTA
}

when the arg is null, it simply returns it, there is no access to tuple's members, so no NPE.