uros-db commented on code in PR #45383:
URL: https://github.com/apache/spark/pull/45383#discussion_r1515609105
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:
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@@ -509,18 +509,10 @@ abstract class StringPredicate extends BinaryExpression
return checkResult
}
// Additional check needed for collation compatibility
- val rightCollationId: Int =
right.dataType.asInstanceOf[StringType].collationId
- if (collationId != rightCollationId) {
- DataTypeMismatch(
- errorSubClass = "COLLATION_MISMATCH",
- messageParameters = Map(
- "collationNameLeft" ->
CollationFactory.fetchCollation(collationId).collationName,
- "collationNameRight" ->
CollationFactory.fetchCollation(rightCollationId).collationName
- )
- )
- } else {
- TypeCheckResult.TypeCheckSuccess
- }
+ val outputCollationId: Int = TypeCoercion
Review Comment:
I'd say `COLLATION_MISMATCH` first, `UNSUPPORTED_COLLATION.FOR_FUNCTION`
second. If the user specifies COLLATION_1 for `left` and COLLATION_2 for
`right`, how would we know which one to use when checking whether the functions
supports this type of collation? (in this case, suppose a function supports
COLLATION_1, but not COLLATION_2 - does the
`UNSUPPORTED_COLLATION.FOR_FUNCTION` pass or fail?)
Hence, I think we would first need to establish that COLLATION_1 and
COLLATION_2 are the same (no `COLLATION_MISMATCH`), before checking whether the
function supports the requested collation (no
`UNSUPPORTED_COLLATION.FOR_FUNCTION`)
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