scala.MatchError on SparkSQL when creating ArrayType of StructType

[invkrh]

Hi,

I am using SparkSQL on 1.1.0 branch.

The following code leads to a scala.MatchError 
at
org.apache.spark.sql.catalyst.expressions.Cast.cast$lzycompute(Cast.scala:247)

val scm = StructType(*inputRDD*.schema.fields.init :+
      StructField("list",
        ArrayType(
          StructType(
            Seq(StructField("*date*", StringType, nullable = *false*),
              StructField("*nbPurchase*", IntegerType, nullable =
*false*)))),
        nullable = false))

// *purchaseRDD* is RDD[sql.ROW] whose schema is corresponding to scm. It is
transformed from *inputRDD*
val schemaRDD = hiveContext.applySchema(purchaseRDD, scm)
schemaRDD.registerTempTable("t_purchase")

Here's the stackTrace:
scala.MatchError: ArrayType(StructType(List(StructField(date,StringType,
*true* ), StructField(n_reachat,IntegerType, *true* ))),true) (of class
org.apache.spark.sql.catalyst.types.ArrayType)
        at
org.apache.spark.sql.catalyst.expressions.Cast.cast$lzycompute(Cast.scala:247)
        at org.apache.spark.sql.catalyst.expressions.Cast.cast(Cast.scala:247)
        at org.apache.spark.sql.catalyst.expressions.Cast.eval(Cast.scala:263)
        at
org.apache.spark.sql.catalyst.expressions.Alias.eval(namedExpressions.scala:84)
        at
org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.apply(Projection.scala:66)
        at
org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.apply(Projection.scala:50)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
        at
org.apache.spark.sql.hive.execution.InsertIntoHiveTable.org$apache$spark$sql$hive$execution$InsertIntoHiveTable$$writeToFile$1(InsertIntoHiveTable.scala:149)
        at
org.apache.spark.sql.hive.execution.InsertIntoHiveTable$$anonfun$saveAsHiveFile$1.apply(InsertIntoHiveTable.scala:158)
        at
org.apache.spark.sql.hive.execution.InsertIntoHiveTable$$anonfun$saveAsHiveFile$1.apply(InsertIntoHiveTable.scala:158)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        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:744)

The strange thing is that *nullable* of *date* and *nbPurchase* field are
set to true while it were false in the code. If I set both to *true*, it
works. But, in fact, they should not be nullable.

Here's what I find at Cast.scala:247 on 1.1.0 branch

  private[this] lazy val cast: Any => Any = dataType match {
    case StringType => castToString
    case BinaryType => castToBinary
    case DecimalType => castToDecimal
    case TimestampType => castToTimestamp
    case BooleanType => castToBoolean
    case ByteType => castToByte
    case ShortType => castToShort
    case IntegerType => castToInt
    case FloatType => castToFloat
    case LongType => castToLong
    case DoubleType => castToDouble
  }

Any idea? Thank you.

Hao



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