Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/6400#discussion_r31001858
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala ---
@@ -31,17 +31,16 @@ import org.apache.spark.sql.{Row, SQLContext}
*/
@DeveloperApi
object RDDConversions {
- def productToRowRdd[A <: Product](data: RDD[A], schema: StructType):
RDD[Row] = {
+ def productToRowRdd[A <: Product](data: RDD[A], outputTypes:
Seq[DataType]): RDD[Row] = {
data.mapPartitions { iterator =>
if (iterator.isEmpty) {
Iterator.empty
} else {
val bufferedIterator = iterator.buffered
- val mutableRow = new
SpecificMutableRow(schema.fields.map(_.dataType))
--- End diff --
I guess the old code used SpecificMutableRow here, but I don't know that
this actually provides a benefit here since we only access it through a generic
interface rather than type-specific setters. AFAIK, we have to return boxed
types from the converters anyways, so I'm not sure that this necessarily helps
us.
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