Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/16057#discussion_r92440234
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -673,48 +673,54 @@ object TypeCoercion {
* If the expression has an incompatible type that cannot be
implicitly cast, return None.
*/
def implicitCast(e: Expression, expectedType: AbstractDataType):
Option[Expression] = {
- val inType = e.dataType
+ implicitCast(e.dataType, expectedType).map { dt =>
+ if (dt == e.dataType) e else Cast(e, dt)
+ }
+ }
+ private def implicitCast(inType: DataType, expectedType:
AbstractDataType): Option[DataType] = {
// Note that ret is nullable to avoid typing a lot of Some(...) in
this local scope.
// We wrap immediately an Option after this.
- @Nullable val ret: Expression = (inType, expectedType) match {
-
+ @Nullable val ret: DataType = (inType, expectedType) match {
// If the expected type is already a parent of the input type, no
need to cast.
- case _ if expectedType.acceptsType(inType) => e
+ case _ if expectedType.acceptsType(inType) => inType
// Cast null type (usually from null literals) into target types
- case (NullType, target) => Cast(e, target.defaultConcreteType)
+ case (NullType, target) => target.defaultConcreteType
// If the function accepts any numeric type and the input is a
string, we follow the hive
// convention and cast that input into a double
- case (StringType, NumericType) => Cast(e,
NumericType.defaultConcreteType)
+ case (StringType, NumericType) => NumericType.defaultConcreteType
// Implicit cast among numeric types. When we reach here, input
type is not acceptable.
// If input is a numeric type but not decimal, and we expect a
decimal type,
// cast the input to decimal.
- case (d: NumericType, DecimalType) => Cast(e,
DecimalType.forType(d))
+ case (d: NumericType, DecimalType) => DecimalType.forType(d)
// For any other numeric types, implicitly cast to each other,
e.g. long -> int, int -> long
- case (_: NumericType, target: NumericType) => Cast(e, target)
+ case (_: NumericType, target: NumericType) => target
// Implicit cast between date time types
- case (DateType, TimestampType) => Cast(e, TimestampType)
- case (TimestampType, DateType) => Cast(e, DateType)
+ case (DateType, TimestampType) => TimestampType
+ case (TimestampType, DateType) => DateType
// Implicit cast from/to string
- case (StringType, DecimalType) => Cast(e,
DecimalType.SYSTEM_DEFAULT)
- case (StringType, target: NumericType) => Cast(e, target)
- case (StringType, DateType) => Cast(e, DateType)
- case (StringType, TimestampType) => Cast(e, TimestampType)
- case (StringType, BinaryType) => Cast(e, BinaryType)
+ case (StringType, DecimalType) => DecimalType.SYSTEM_DEFAULT
+ case (StringType, target: NumericType) => target
+ case (StringType, DateType) => DateType
+ case (StringType, TimestampType) => TimestampType
+ case (StringType, BinaryType) => BinaryType
// Cast any atomic type to string.
- case (any: AtomicType, StringType) if any != StringType => Cast(e,
StringType)
+ case (any: AtomicType, StringType) if any != StringType =>
StringType
// When we reach here, input type is not acceptable for any types
in this type collection,
// try to find the first one we can implicitly cast.
- case (_, TypeCollection(types)) => types.flatMap(implicitCast(e,
_)).headOption.orNull
+ case (_, TypeCollection(types)) =>
+ types.flatMap(implicitCast(inType, _)).headOption.orNull
+
+ case (ArrayType(dt1, n1), ArrayType(dt2: DataType, n2)) if n2 ||
!n1 =>
--- End diff --
Some casts can always produce a null, for example casting `Double.Inf` to
`Long` will result in a null. We need to check if this nullability does not
cause any problems with `ArrayType.containsNull`. See @viirya previous comment
on this.
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