viirya commented on a change in pull request #34038:
URL: https://github.com/apache/spark/pull/34038#discussion_r712593090
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
##########
@@ -401,16 +401,30 @@ trait CheckAnalysis extends PredicateHelper with
LookupCatalog {
|the ${ordinalNumber(ti + 1)} table has
${child.output.length} columns
""".stripMargin.replace("\n", " ").trim())
}
+ val isUnion = operator.isInstanceOf[Union]
// Check if the data types match.
- dataTypes(child).zip(ref).zipWithIndex.foreach { case ((dt1,
dt2), ci) =>
- // SPARK-18058: we shall not care about the nullability of
columns
- if (TypeCoercion.findWiderTypeForTwo(dt1.asNullable,
dt2.asNullable).isEmpty) {
- failAnalysis(
- s"""
- |${operator.nodeName} can only be performed on tables
with the compatible
- |column types. ${dt1.catalogString} <>
${dt2.catalogString} at the
- |${ordinalNumber(ci)} column of the ${ordinalNumber(ti +
1)} table
- """.stripMargin.replace("\n", " ").trim())
+ if (!isUnion) {
Review comment:
I think these set operations work basically the same. The by-position
resolution for union, I think, is to follow SQL. It only requires the columns
to union have the same data types in same order, but not column names.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
