sunchao commented on a change in pull request #32764:
URL: https://github.com/apache/spark/pull/32764#discussion_r645723665
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
##########
@@ -2169,12 +2169,29 @@ class Analyzer(override val catalogManager:
CatalogManager)
unbound, arguments, unsupported)
}
+ if (bound.inputTypes().length != arguments.length) {
+ throw
QueryCompilationErrors.v2FunctionInvalidInputTypeLengthError(
+ bound, arguments)
+ }
+
+ val castedArguments = arguments.zip(bound.inputTypes()).map
{ case (arg, ty) =>
+ if (arg.dataType != ty) {
+ if (Cast.canCast(arg.dataType, ty)) {
+ Cast(arg, ty)
+ } else {
+ throw
QueryCompilationErrors.v2FunctionCastError(bound, arg, ty)
+ }
+ } else {
+ arg
+ }
+ }
Review comment:
@cloud-fan I think this approach will not allow us to handle function
with varargs, for instance: `max(int, long, float, double, int, long, long,
double)`. For this scenario, `bind` can check the input arguments and return a
proper implementation of the function (although we still need to do something
extra for varargs in Spark).
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