dtenedor commented on a change in pull request #35735:
URL: https://github.com/apache/spark/pull/35735#discussion_r820987567
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HistogramNumeric.scala
##########
@@ -125,7 +125,21 @@ case class HistogramNumeric(
} else {
val result = (0 until buffer.getUsedBins).map { index =>
val coord = buffer.getBin(index)
- InternalRow.apply(coord.x, coord.y)
+ // The 'coord.x' and 'coord.y' have double type here. If the
expression is expected to
+ // return a result of double type, this is sufficient. Otherwise, we
need to internally
+ // convert these values to the expected result type, for cases like
timestamps and intervals
+ // which are valid inputs to the numeric histogram aggregate function.
+ val result: Any = left.dataType match {
+ case ByteType => coord.x.toByte
+ case IntegerType | DateType | _: YearMonthIntervalType =>
+ coord.x.toInt
Review comment:
Good idea, done. Also added a similar example in a comment for the
baseline code path when the new SQLConf is turned off.
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