[SPARK-18251] DataSet API | RuntimeException: Null value appeared in non-nullable field when holding Option Case Class - ASF JIRA

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Details

Type: Bug
Status: Resolved
Priority: Major
Resolution: Fixed
Affects Version/s: 2.0.1
Fix Version/s: 2.2.0
Component/s: Spark Core
Labels:
None
Environment:

OS X

Description

I am running into a runtime exception when a DataSet is holding an Empty object instance for an Option type that is holding non-nullable field. For instance, if we have the following case class:

case class DataRow(id: Int, value: String)

Then, DataSet[Option[DataRow]] can only hold Some(DataRow) objects and cannot hold Empty. If it does so, the following exception is thrown:

Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 0.0 failed 1 times, most recent failure: Lost task 6.0 in stage 0.0 (TID 6, localhost): java.lang.RuntimeException: Null value appeared in non-nullable field:
- field (class: "scala.Int", name: "id")
- option value class: "DataSetOptBug.DataRow"
- root class: "scala.Option"
If the schema is inferred from a Scala tuple/case class, or a Java bean, please try to use scala.Option[_] or other nullable types (e.g. java.lang.Integer instead of int/scala.Int).
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
	at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
	at org.apache.spark.scheduler.Task.run(Task.scala:86)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
	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)

The bug can be reproduce by using the program: https://gist.github.com/aniketbhatnagar/2ed74613f70d2defe999c18afaa4816e