cloud-fan commented on code in PR #58408:
URL: https://github.com/apache/spark/pull/58408#discussion_r3935947641
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:
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@@ -2404,7 +2412,12 @@ case class FormatString(children: Expression*) extends
Expression with ImplicitC
val numArgLists = argListGen.length
val argListCode = argListGen.zipWithIndex.map { case(v, index) =>
val value =
- if (CodeGenerator.boxedType(v._1) != CodeGenerator.javaType(v._1)) {
+ if (UserDefinedType.sqlType(v._1).isInstanceOf[DecimalType]) {
Review Comment:
**Non-blocking (P2):** `FormatString` accepts `AnyDataType`, so an
object-typed Spark `Decimal` can reach this branch, for example through
`Literal.fromObject(Decimal("1.5"))`. The interpreted path converts that
runtime value and formats `%f` successfully, but this declared-type check
leaves generated code passing Spark `Decimal` to `Formatter`, which throws
`IllegalFormatConversionException`. Please cover this admitted `ObjectType`
case in generated conversion as well and add an interpreted/codegen regression
with an object-typed decimal literal.
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