amaliujia commented on code in PR #40693:
URL: https://github.com/apache/spark/pull/40693#discussion_r1162331907
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
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@@ -820,11 +821,13 @@ case class Divide(
}
private lazy val div: (Any, Any) => Any = dataType match {
- case d @ DecimalType.Fixed(precision, scale) => (l, r) => {
- val value = d.fractional.asInstanceOf[Fractional[Any]].div(l, r)
- checkDecimalOverflow(value.asInstanceOf[Decimal], precision, scale)
- }
- case ft: FractionalType => ft.fractional.asInstanceOf[Fractional[Any]].div
+ case d @ DecimalType.Fixed(precision, scale) =>
+ val fractional = PhysicalDecimalType(precision, scale).fractional
+ (l, r) => {
+ val value = fractional.asInstanceOf[Fractional[Any]].div(l, r)
Review Comment:
If you think this is better, we can still does
`PhysicalFrancitonalType.franctional(dt: Datatype)` which does a resolution but
hide the `asInstanceOf[Fractional[Any]]`?
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