Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7179#discussion_r33749911
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CodeGenerationSuite.scala
---
@@ -42,4 +47,47 @@ class CodeGenerationSuite extends SparkFunSuite {
futures.foreach(Await.result(_, 10.seconds))
}
+
+ // Test GenerateOrdering for all common types. For each type, we
construct random input rows that
+ // contain two columns of that type, then for pairs of
randomly-generated rows we check that
+ // GenerateOrdering agrees with RowOrdering.
+ (DataTypeTestUtils.atomicTypes ++ Set(NullType)).foreach { dataType =>
+ test(s"GenerateOrdering with $dataType") {
+ val rowOrdering = RowOrdering.forSchema(Seq(dataType, dataType))
+ val genOrdering = GenerateOrdering.generate(
+ BoundReference(0, dataType, nullable = true).asc ::
+ BoundReference(1, dataType, nullable = true).asc :: Nil)
+ val rowType = StructType(
+ StructField("a", dataType, nullable = true) ::
+ StructField("b", dataType, nullable = true) :: Nil)
+ val toCatalyst =
CatalystTypeConverters.createToCatalystConverter(rowType)
+ // Sort ordering is not defined for NaN, so skip any random inputs
that contain it:
+ def isIncomparable(v: Any): Boolean = v match {
--- End diff --
While working on this, I discovered that `RowOrdering` and
`GenerateOrdering` disagree for inputs containing NaN. This isn't a bug per-se,
since many systems have undefined behavior when sorting on NaN. For this
reason, I think that some databases prohibit NaN and Infinity from being used.
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