ulysses-you commented on code in PR #36856:
URL: https://github.com/apache/spark/pull/36856#discussion_r896333392
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
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@@ -53,6 +53,17 @@ case class UnaryMinus(
override def toString: String = s"-$child"
private lazy val numeric = TypeUtils.getNumeric(dataType, failOnError)
+ private lazy val unaryMinusFunc: Any => Any = dataType match {
Review Comment:
Do you mean rewrite it to ?
```scala
private def unaryMinusFunc: Any => Any = dataType match {
......
```
The reason I pull out and make it as lazy val is: the data type is known
before do eval in an expression. Let's say if the data type is integer,
- then the function can be elimiated to `input => numeric.negate(input)`
during execution
- if you declare it as a function, then the function would be during
execution:
```scala
dataType match {
....
case _ => input => numeric.negate(input)
```
The overhead is not about creating a function, but the data type matching
elimination. So I think the lazy val is more efficient ?
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