cloud-fan commented on code in PR #50959:
URL: https://github.com/apache/spark/pull/50959#discussion_r2113185354
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ResolveDefaultColumnsUtil.scala:
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@@ -432,18 +432,34 @@ object ResolveDefaultColumns extends QueryErrorsBase
targetType: DataType,
colName: String): Option[Expression] = {
expr match {
- case l: Literal if !Seq(targetType, l.dataType).exists(_ match {
+ case l: Literal => defaultValueFromWiderType(l, targetType, colName)
+ case _ => None
+ }
+ }
+
+ /**
+ * If the provided default value is a literal of a wider type than the
target column,
+ * but the literal value fits within the narrower type, just coerce it for
convenience.
+ * Exclude boolean/array/struct/map types from consideration for this type
coercion to
+ * avoid surprising behavior like interpreting "false" as integer zero.
+ */
+ def defaultValueFromWiderType(
+ expr: Expression,
+ targetType: DataType,
+ colName: String): Option[Expression] = {
+ expr match {
+ case e if !Seq(targetType, e.dataType).exists(_ match {
case _: BooleanType | _: ArrayType | _: StructType | _: MapType => true
case _ => false
}) =>
- val casted = Cast(l, targetType, Some(conf.sessionLocalTimeZone),
evalMode = EvalMode.TRY)
+ val casted = Cast(e, targetType, Some(conf.sessionLocalTimeZone),
evalMode = EvalMode.TRY)
Review Comment:
This means that the input `expr` must be foldable, but we didn't check it.
I don't think we need two methods. We can just extend the existing
`defaultValueFromWiderTypeLiteral`. But instead of matching `Literal`, we match
foldable expressions.
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