Github user nongli commented on a diff in the pull request:
https://github.com/apache/spark/pull/11435#discussion_r54950960
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala ---
@@ -149,14 +149,55 @@ private[sql] case class PhysicalRDD(
ctx.INPUT_ROW = row
ctx.currentVars = null
val columns = exprs.map(_.gen(ctx))
+
+ // The input RDD can either return (all) ColumnarBatches or
InternalRows. We determine this
+ // by looking at the first value of the RDD and then calling the
function which will process
+ // the remaining. It is faster to return batches.
+ // TODO: The abstractions between this class and SqlNewHadoopRDD makes
it difficult to know
--- End diff --
I think we need to clean this up but let's do this in a follow up. That
counter is too expensive to maintain right now and it's not clear why we would
if we maintain sql metrics.
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