andygrove commented on code in PR #6563:
URL: https://github.com/apache/datafusion-comet/pull/6563#discussion_r4199344431


##########
spark/src/main/scala/org/apache/comet/serde/arrays.scala:
##########
@@ -540,39 +540,73 @@ object CometSlice extends CometExpressionSerde[Slice] {
 
 private[comet] object ArraySetSupport {
   val floatingPointReason: String =
-    "Floating-point elements match Spark's signed-zero and NaN semantics 
natively only on " +
-      "Spark 4.2.0, whose optimizer normalizes the arguments (SPARK-54918)"
-
-  // The native kernels match Spark only when the plan has already normalized 
the arguments, and
-  // only Spark 4.2.0 does that (SPARK-54918). Earlier releases keep flat 
signed zeros apart.
-  // From 4.0.5, 4.1.4 and 4.2.1, SPARK-59602 normalizes during evaluation 
instead, which the
-  // native kernels do not match for NaN payloads or nested zeros. A top-level
-  // KnownFloatingPointNormalized marker cannot replace the version check: 
Spark also normalizes
-  // CreateArray, If, CaseWhen, and Coalesce recursively without wrapping the 
resulting array.
-  def normalizesArgumentsInPlan(version: String): Boolean =
-    Utils.majorMinorPatchVersion(version).contains((4, 2, 0))
+    "Floating-point elements match Spark's signed-zero semantics natively only 
on Spark " +
+      "4.0.5+, 4.1.4+ and 4.2+, which treat -0.0 and 0.0 as one value in these 
functions " +
+      "(SPARK-54918, SPARK-59602)"
+
+  val collationReason: String =
+    "Elements that hold both a floating-point value and a non-UTF8_BINARY 
collated string fall " +
+      "back to Spark, which compares the strings under their collation, while 
Comet's native " +
+      "kernels compare their raw bytes"
+
+  // Spark 4.2.0 normalizes the arguments of these functions in the plan 
(SPARK-54918), and 4.0.5,
+  // 4.1.4 and 4.2.1 normalize while evaluating them (SPARK-59602). Either 
way, Spark treats -0.0
+  // and 0.0, and every NaN, as one value at any depth, which the spark_ 
variants match. Earlier
+  // releases keep -0.0 and 0.0 apart in a flat array. The check reads the 
version rather than a
+  // KnownFloatingPointNormalized marker, because SPARK-59602 adds no marker, 
and SPARK-54918
+  // normalizes CreateArray, If, CaseWhen and Coalesce without wrapping the 
resulting array.
+  def normalizesFloats(version: String): Boolean =
+    Utils.majorMinorPatchVersion(version).exists {
+      case (4, 0, patch) => patch >= 5
+      case (4, 1, patch) => patch >= 4

Review Comment:
   I added the guard here after all (88ec62982). `CometArrayUnion` now wraps 
the call in `CASE WHEN <left> IS NOT NULL`, as `CometElementAt` does, unless 
the right operand is a column or a literal, which can't throw. A nullable 
nondeterministic left operand stays on Spark, since the guard would evaluate it 
twice. The guard covers every element type, so it also fixes the `array_union` 
case of #6613. `array_union_null_left.sql` runs your query for `ARRAY<INT>` and 
`ARRAY<DOUBLE>`, plus a batch where the guard selects only some rows, and 
`array_union_null_left_ansi.sql` runs the ANSI cast. Both fail without the 
guard, and the array fixtures and suites pass on 4.1 and 4.2.
   



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