cloud-fan commented on code in PR #37439:
URL: https://github.com/apache/spark/pull/37439#discussion_r958617662
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCastInBinaryComparison.scala:
##########
@@ -316,55 +316,25 @@ object UnwrapCastInBinaryComparison extends
Rule[LogicalPlan] {
// note that 3.14 will be rounded to 3.14000010... after casting to
float
val (nullList, canCastList) = (ArrayBuffer[Literal](),
ArrayBuffer[Literal]())
- var containsCannotCastLiteral = false
val fromType = fromExp.dataType
val ordering = toType.ordering.asInstanceOf[Ordering[Any]]
- val minMaxInToType = getRange(fromType).map {
- case (min, max) =>
- (Cast(Literal(min), toType).eval(), Cast(Literal(max), toType).eval())
- }
list.foreach {
case lit @ Literal(null, _) => nullList += lit
case NonNullLiteral(value, _) =>
- val minMaxCmp = minMaxInToType.map {
- case (minInToType, maxInToType) =>
- (ordering.compare(value, minInToType), ordering.compare(value,
maxInToType))
- }
- minMaxCmp match {
- // the literal value is out of fromType range
- case Some((minCmp, maxCmp)) if maxCmp > 0 || minCmp < 0 =>
- containsCannotCastLiteral = true
- case _ =>
- val newValue = Cast(Literal(value), fromType, ansiEnabled =
false).eval()
- if (newValue == null) {
- // the literal cannot cast to fromExp.dataType, and there is no
min/max for the
- // fromType
- containsCannotCastLiteral = true
- } else {
- val valueRoundTrip = Cast(Literal(newValue, fromType),
toType).eval()
- val cmp = ordering.compare(value, valueRoundTrip)
- if (cmp == 0) {
- canCastList += Literal(newValue, fromType)
- } else {
- // the literal value is rounded up/down after casting to
`fromType`
- containsCannotCastLiteral = true
- }
- }
+ val newValue = Cast(Literal(value), fromType, ansiEnabled =
false).eval()
Review Comment:
does it mean we can always use `Cast` to detect "castable" and the
range-related check is not needed?
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