stefankandic commented on code in PR #45549:
URL: https://github.com/apache/spark/pull/45549#discussion_r1535334643
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFloatingNumbers.scala:
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@@ -144,6 +142,17 @@ object NormalizeFloatingNumbers extends Rule[LogicalPlan] {
val function = normalize(lv)
KnownFloatingPointNormalized(ArrayTransform(expr,
LambdaFunction(function, Seq(lv))))
+ case _ if expr.dataType.isInstanceOf[MapType] =>
+ val MapType(kt, vt, containsNull) = expr.dataType
+ val lv1 = NamedLambdaVariable("arg", kt, containsNull)
+ val lv2 = NamedLambdaVariable("arg", vt, containsNull)
+ val functionL1 = normalize(lv1)
+ val functionL2 = normalize(lv2)
+ KnownFloatingPointNormalized(
Review Comment:
if i'm reading this correctly this will return an array and not a map - we
should probably want to do normalization on keys and values separately and then
create a new map out of those right?
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