sathiyapk commented on a change in pull request #34729:
URL: https://github.com/apache/spark/pull/34729#discussion_r772972255
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala
##########
@@ -249,9 +249,9 @@ case class Cbrt(child: Expression) extends
UnaryMathExpression(math.cbrt, "CBRT"
""",
since = "1.4.0",
group = "math_funcs")
-case class Ceil(child: Expression) extends UnaryMathExpression(math.ceil,
"CEIL") {
+ case class Ceil(child: Expression) extends UnaryMathExpression(math.ceil,
"CEIL") {
override def dataType: DataType = child.dataType match {
Review comment:
I thought the same, but the `eval` of RoundBase does it.
```
override def eval(input: InternalRow): Any = {
if (scaleV == null) { // if scale is null, no need to eval its child at
all
null
} else {
val evalE = child.eval(input)
if (evalE == null) {
null
} else {
nullSafeEval(evalE)
}
}
}
```
So if we must define the data type of the return expression, we could do
something like :
```
if (scaleV == null) return Literal.create(null, dtNullScale(child.dataType))
def dtNullScale(dt: DataType): DataType = dt match {
case _ : FloatType | _ : DoubleType => DoubleType
case _ => LongType
}
```
What do you think ?
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