stefankandic commented on code in PR #48585:
URL: https://github.com/apache/spark/pull/48585#discussion_r1812115111
##########
sql/core/src/test/scala/org/apache/spark/sql/CollationSQLExpressionsSuite.scala:
##########
@@ -3260,6 +3260,72 @@ class CollationSQLExpressionsSuite
}
}
+ test("SPARK-50060: set operators with conflicting and non-conflicting
collations") {
+ val setOperators = Seq[(String, Seq[Row])](
+ ("UNION", Seq(Row("a"))),
+ ("INTERSECT", Seq(Row("a"))),
+ ("EXCEPT", Seq()),
+ ("UNION ALL", Seq(Row("A"), Row("a"))),
+ ("INTERSECT ALL", Seq(Row("a"))),
+ ("EXCEPT ALL", Seq()),
+ ("UNION DISTINCT", Seq(Row("a"))),
+ ("INTERSECT DISTINCT", Seq(Row("a"))),
+ ("EXCEPT DISTINCT", Seq()))
+
+ Seq[Boolean](true, false).foreach{ ansi_enabled =>
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> ansi_enabled.toString,
+ SqlApiConf.DEFAULT_COLLATION -> "UNICODE") {
+ setOperators.foreach { case (operator, result) =>
Review Comment:
sorry for not catching this earlier but in cases where we have multiple
nested for each calls we can just wrap all of them in a for loop like:
```code
for {
ansiEnabled <- Seq(true, false)
(operator, result) <- setOperators
} {
withSQLConf(
SQLConf.ANSI_ENABLED.key -> ansiEnabled.toString,
SqlApiConf.DEFAULT_COLLATION -> "UNICODE"
) {
// some code
}
}
```
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