scala - Spark 2.0-2.3 数据集 groupByKey 和 mapGroups

Question

当我在本地运行时，我看到了正确的记录输出。但是，当我在集群上运行时，输出是不同的，并且看起来不一致。甚至某些 mappedGroup 输出也是正确的。这是火花闭包的问题吗？不知道如何最好地描述我所看到的。

我可能不理解 mapGroups 并且并非每个组的所有值都进入 recordList 变量。

case class MyCaseClass (keyValue: int,c2: String,c3: String,c4: Double)

case class NewClass (thing1:String,thing2:String,thing3:String,thing4:String)

case class WorkTodo(myClassRecords: Seq[MyCaseClass]){
    def toNewRecords: Seq[NewClass] = {
    //e.g. work that requires all MyCaseClass.keyValue=1 to be in the list. 
    //This function would create new Java Objects to perform calculations and eventually output a set of NewClass records
}

val processedRecords = ds.as[MyCaseClass].groupByKey(_.keyValue)
      .mapGroups {
      case (v, iter) => {
        var recordList = new ListBuffer[MyCaseClass]
        iter.foreach {x=>
          recordList += MyCaseClass(x.keyValue,x.c2,x.c3,x.c4)
        }

        WorkToDo(recordList).toNewRecords 
      }
    }

PS 欢迎任何其他仍然使用数据集的解决方案:)