ulysses-you commented on code in PR #36698:
URL: https://github.com/apache/spark/pull/36698#discussion_r885447945
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
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@@ -490,10 +621,26 @@ trait DivModLike extends BinaryArithmetic {
s"${eval2.value} == 0"
}
val javaType = CodeGenerator.javaType(dataType)
- val operation = if (operandsDataType.isInstanceOf[DecimalType]) {
-
decimalToDataTypeCodeGen(s"${eval1.value}.$decimalMethod(${eval2.value})")
+ val checkOverflow = if (operandsDataType.isInstanceOf[DecimalType]) {
+ val decimal = super.dataType.asInstanceOf[DecimalType]
+ val errorContextCode = if (nullOnOverflow) {
+ "\"\""
+ } else {
+ ctx.addReferenceObj("errCtx", queryContext)
+ }
+ val decimalValue = ctx.freshName("decimalValue")
+ // scalastyle:off line.size.limit
+ s"""
+ |${CodeGenerator.javaType(decimal)} $decimalValue =
${eval1.value}.$decimalMethod(${eval2.value}).toPrecision(
Review Comment:
The data type may different, e.g. the ev of `IntegralDivide` is long but
`Divide` is decimal if the input type is decimal. So here use a temp decimal
type varible.
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