mingmwang commented on PR #6331:
URL:
https://github.com/apache/arrow-datafusion/pull/6331#issuecomment-1543398311
```spark
override def resultDecimalType(p1: Int, s1: Int, p2: Int, s2: Int):
DecimalType = {
val resultScale = s1 + s2
val resultPrecision = p1 + p2 + 1
if (allowPrecisionLoss) {
DecimalType.adjustPrecisionScale(resultPrecision, resultScale)
} else {
DecimalType.bounded(resultPrecision, resultScale)
}
}
private lazy val numeric = TypeUtils.getNumeric(dataType, failOnError)
protected override def nullSafeEval(input1: Any, input2: Any): Any =
dataType match {
case DecimalType.Fixed(precision, scale) =>
checkDecimalOverflow(numeric.times(input1,
input2).asInstanceOf[Decimal], precision, scale)
case _: IntegerType if failOnError =>
MathUtils.multiplyExact(
input1.asInstanceOf[Int],
input2.asInstanceOf[Int],
getContextOrNull())
case _: LongType if failOnError =>
MathUtils.multiplyExact(
input1.asInstanceOf[Long],
input2.asInstanceOf[Long],
getContextOrNull())
case _ => numeric.times(input1, input2)
}
```
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