A value of a row can be accessed through both generic access by ordinal,
which will incur boxing overhead for primitives, as well as native
primitive access. An example of generic access by ordinal:
import org.apache.spark.sql._
val row = Row(1, true, "a string", null)
// row: Row = [1,true,a
the Spark-SQL Row trait has a schema that by default is null. when the
schema is null operations that rely on fieldIndex such as
getAs[T](fieldName: String): T do not work.
i noticed that when i convert a DataFrame to Rdd[Row] that the Row objects
do have schemas. can i rely on this?
when can i b
