将数据加载到Spark DataFrame中时，DataType不匹配异常

Question

我有以下数据，其返回类型为Array（Array（AnyRef））。 第二行具有基础数据集的数据类型。 我想将数据读入spark数据框。 但是，我在执行此操作时遇到以下异常。

线程“ main” scala中的异常。MatchError：StringType（类java.lang.String）

有什么建议可以克服吗？???

var data = getData
val df = getTable(data, spark)
df.printSchema()
df.show()
def getData: Array[Array[AnyRef]] =

Array[Array[AnyRef]](Array("MS_FUND_ID", "MS_INVESTMENT_TYPE", "CURRENCY", "MS_CAT_ID", "date", "MS_NETFLOWS_FUND", "MS_AUM_FUND"),
  Array("StringType", "StringType", "StringType", "StringType", "StringType", "DoubleType", "DoubleType"),
  Array("F00000MLKR", "OE", "USD", "C1", "2017-10-31", "10", "15"),
  Array("F00000MLKS", "OE", "USD", "C1", "2017-10-31", "-10", "10"),
  Array("F00000MLKS", "OX", "USD", "C1", "2017-10-31", "-10", "10"),
  Array("F00000MLKT", "INS", "USD", "C1", "2017-10-31", "30", "50"))


def getTable(table: Array[Array[AnyRef]], spark: SparkSession): DataFrame = 

{ 

val fields = new util.ArrayList[StructField]
val fieldNames = table(0)
var fieldTypes = table(1)

fieldTypes = fieldTypes.map {
  case x: DoubleType => x.asInstanceOf[DoubleType]
  case x: StringType => x.asInstanceOf[StringType]
}
var f = 0
while ( {
  f < table(0).length
}) {
  var fn = fieldNames(f).toString
  var ft = fieldTypes(f).asInstanceOf[DataType]
  fields.add(StructField(fn, ft, true, Metadata.empty))

  {
    f += 1;
    f - 1
  }
}
val schema1 = new StructType(fields.toArray(new Array[StructField](fields.size)))
println(schema1)
val rows = new util.ArrayList[Row]
var r = 2
while ( {
  r < table.length
}) {
  val data = table(r)
  rows.add(new GenericRowWithSchema(data.asInstanceOf[Array[Any]], schema1))

  {
    r += 1;
    r - 1
  }
}
var i = 0
while ( {
  i < rows.size
}) {
  System.out.println("Rows : " + rows.get(i))

  {
    i += 1;
    i - 1
  }
}
val DF = spark.createDataFrame(rows, schema1)
DF

} '''