Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/17713#discussion_r115154162
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
---
@@ -137,32 +137,46 @@ case class In(value: Expression, list:
Seq[Expression]) extends Predicate {
require(list != null, "list should not be null")
override def checkInputDataTypes(): TypeCheckResult = {
list match {
- case ListQuery(sub, _, _) :: Nil =>
+ case ListQuery(sub, _, exprId) :: Nil =>
val valExprs = value match {
case cns: CreateNamedStruct => cns.valExprs
case expr => Seq(expr)
}
-
- val mismatchedColumns = valExprs.zip(sub.output).flatMap {
- case (l, r) if l.dataType != r.dataType =>
- s"(${l.sql}:${l.dataType.catalogString},
${r.sql}:${r.dataType.catalogString})"
- case _ => None
- }
-
- if (mismatchedColumns.nonEmpty) {
+ if (valExprs.length != sub.output.length) {
TypeCheckResult.TypeCheckFailure(
s"""
- |The data type of one or more elements in the left hand
side of an IN subquery
- |is not compatible with the data type of the output of the
subquery
- |Mismatched columns:
- |[${mismatchedColumns.mkString(", ")}]
- |Left side:
- |[${valExprs.map(_.dataType.catalogString).mkString(", ")}].
- |Right side:
- |[${sub.output.map(_.dataType.catalogString).mkString(",
")}].
+ |The number of columns the left hand side of an IN subquery
does not match the
+ |number of columns in the output of subquery.
+ |#columns in left hand side: ${valExprs.length}.
+ |#columns in right hand side: ${sub.output.length}.
+ |Left side columns:
+ |[${valExprs.map(_.sql).mkString(", ")}].
+ |Right side columns:
+ |[${sub.output.map(_.sql).mkString(", ")}].
+ |Subquery expression id: #${exprId.id}
--- End diff --
`Subquery expression id: #${exprId.id}` does not help to the end users, I
think
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