Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16777#discussion_r100861589
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -117,49 +115,67 @@ object TypeCoercion {
* loss of precision when widening decimal and double, and promotion to
string.
*/
private[analysis] def findWiderTypeForTwo(t1: DataType, t2: DataType):
Option[DataType] = {
- (t1, t2) match {
- case (t1: DecimalType, t2: DecimalType) =>
- Some(DecimalPrecision.widerDecimalType(t1, t2))
- case (t: IntegralType, d: DecimalType) =>
- Some(DecimalPrecision.widerDecimalType(DecimalType.forType(t), d))
- case (d: DecimalType, t: IntegralType) =>
- Some(DecimalPrecision.widerDecimalType(DecimalType.forType(t), d))
- case (_: FractionalType, _: DecimalType) | (_: DecimalType, _:
FractionalType) =>
- Some(DoubleType)
- case _ =>
- findTightestCommonTypeToString(t1, t2)
- }
+ findTightestCommonType(t1, t2)
+ .orElse(findWiderTypeForDecimal(t1, t2))
--- End diff --
yea we changed the order, but looks like it won't change the result.
`findWiderTypeForDecimal` will always return a result for decimal type and
numeric type, and if `findTightestCommonType` can return a result,
`findWiderTypeForDecimal` will return the same result. So it doesn't matter if
we run `findTightestCommonType` before or after it.
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