Github user rjurney commented on the pull request:
https://github.com/apache/spark/pull/455#issuecomment-49698081
It also looks like we need a custom function to handle the UNION type. I've
extended what you wrote for DOUBLE/FLOAT:
def unpack(value: Any, schema: Schema): Any = schema.getType match {
case STRING => value.asInstanceOf[java.lang.String]
case ENUM => value.toString
case LONG => value.asInstanceOf[java.lang.Long]
case INT => value.asInstanceOf[java.lang.Integer]
case FLOAT => value.asInstanceOf[java.lang.Float]
case DOUBLE => value.asInstanceOf[java.lang.Double]
case ARRAY => unpackArray(value, schema.getElementType)
case RECORD => unpackRecord(value.asInstanceOf[GenericRecord])
case _ => value.toString
}
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