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[SPARK-52233][SQL] Fix map_zip_with for Floating Point Types #50967

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[SPARK-52233][SQL] Fix map_zip_with for Floating Point Types #50967

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f2d1ab3
Fix map_zip_with
mihailom-db May 21, 2025
f9d5c72
Refactor
mihailom-db May 21, 2025
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33 changes: 25 additions & 8 deletions ...alyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/higherOrderFunctions.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -1124,23 +1124,40 @@ case class MapZipWith(left: Expression, right: Expression, function: Expression)

private def getKeysWithIndexesFast(keys1: ArrayData, keys2: ArrayData) = {
val hashMap = new mutable.LinkedHashMap[Any, Array[Option[Int]]]
val NaNTracker = Array[Option[Int]](None, None)
for ((z, array) <- Array((0, keys1), (1, keys2))) {
var i = 0
while (i < array.numElements()) {
val key = array.get(i, keyType)
hashMap.get(key) match {
case Some(indexes) =>
if (indexes(z).isEmpty) {
indexes(z) = Some(i)
keyType match {
case FloatType if key.asInstanceOf[Float].isNaN =>
NaNTracker(z) = Some(i)
case DoubleType if key.asInstanceOf[Double].isNaN =>
NaNTracker(z) = Some(i)
case _ =>
hashMap.get(key) match {
case Some(indexes) =>
if (indexes(z).isEmpty) {
indexes(z) = Some(i)
}
case None =>
val indexes = Array[Option[Int]](None, None)
indexes(z) = Some(i)
hashMap.put(key, indexes)
}
case None =>
val indexes = Array[Option[Int]](None, None)
indexes(z) = Some(i)
hashMap.put(key, indexes)
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My proposal is to simply do

val normalized = if (key == Float.NaN) {
  Float.NaN
} else if (key == Double.NaN) {
  Double.NaN
} else {
  key
}
hashMap.put(key, indexes)

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The idea is to use the same NaN instance, so that the hash map can work out of the box.

}
i += 1
}
}
if (NaNTracker(0).isDefined || NaNTracker(1).isDefined) {
keyType match {
case FloatType =>
hashMap.put(Float.NaN, NaNTracker)
case DoubleType =>
hashMap.put(Double.NaN, NaNTracker)
case _ =>
}
}
hashMap
}

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