Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/20350#discussion_r163013386
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala ---
@@ -237,14 +238,26 @@ final class Decimal extends Ordered[Decimal] with
Serializable {
/**
* Create new `Decimal` with given precision and scale.
*
- * @return a non-null `Decimal` value if successful or `null` if
overflow would occur.
+ * @return a non-null `Decimal` value if successful. Otherwise, if
`nullOnOverflow` is true, null
+ * is returned; if `nullOnOverflow` is false, an
`ArithmeticException` is thrown.
*/
private[sql] def toPrecision(
precision: Int,
scale: Int,
- roundMode: BigDecimal.RoundingMode.Value = ROUND_HALF_UP): Decimal =
{
+ roundMode: BigDecimal.RoundingMode.Value = ROUND_HALF_UP,
+ nullOnOverflow: Boolean = true): Decimal = {
val copy = clone()
- if (copy.changePrecision(precision, scale, roundMode)) copy else null
+ if (copy.changePrecision(precision, scale, roundMode)) {
+ copy
+ } else {
+ val message = s"$toDebugString cannot be represented as
Decimal($precision, $scale)."
+ if (nullOnOverflow) {
+ logWarning(s"$message NULL is returned.")
--- End diff --
I am ok with using debug/trace level logging. Can you make sure we do not
construct the message unless we are logging or throwing the exception (changing
`val` into `def` should be enough)?
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