mgaido91 commented on a change in pull request #24636: [SPARK-27684][SQL] Avoid
conversion overhead for primitive types
URL: https://github.com/apache/spark/pull/24636#discussion_r287422450
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala
##########
@@ -1003,22 +1003,38 @@ case class ScalaUDF(
// such as IntegerType, its javaType is `int` and the returned type of
user-defined
// function is Object. Trying to convert an Object to `int` will cause
casting exception.
val evalCode = evals.map(_.code).mkString("\n")
- val (funcArgs, initArgs) = evals.zipWithIndex.map { case (eval, i) =>
- val argTerm = ctx.freshName("arg")
- val convert = s"$convertersTerm[$i].apply(${eval.value})"
- val initArg = s"Object $argTerm = ${eval.isNull} ? null : $convert;"
- (argTerm, initArg)
+ val (funcArgs, initArgs) =
evals.zipWithIndex.zip(children.map(_.dataType)).map {
+ case ((eval, i), dt) =>
+ val argTerm = ctx.freshName("arg")
+ val initArg = if (CatalystTypeConverters.isPrimitive(dt)) {
+ val convertedTerm = ctx.freshName("conv")
+ s"""
+ |${CodeGenerator.boxedType(dt)} $convertedTerm = ${eval.value};
+ |Object $argTerm = ${eval.isNull} ? null : $convertedTerm;
Review comment:
I agree with @JoshRosen . It would be better to define a generic approach
for addressing this and there are several instances of it. I can create another
JIRA and start a PR for that if you're ok with it.
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