[SPARK-28344][SQL][FOLLOW-UP] Check the ambiguous self-join only if there is a join in the plan

sql/core/src/main/scala/org/apache/spark/sql/execution/analysis/DetectAmbiguousSelfJoin.scala

@@ -76,6 +76,8 @@ class DetectAmbiguousSelfJoin(conf: SQLConf) extends Rule[LogicalPlan] {
     // We always remove the special metadata from `AttributeReference` at the end of this rule, so
     // Dataset column reference only exists in the root node via Dataset transformations like
     // `Dataset#select`.
+    if (plan.find(_.isInstanceOf[Join]).isEmpty) return stripColumnReferenceMetadataInPlan(plan)
+
     val colRefAttrs = plan.expressions.flatMap(_.collect {
       case a: AttributeReference if isColumnReference(a) => a
     })
@@ -153,6 +155,10 @@ class DetectAmbiguousSelfJoin(conf: SQLConf) extends Rule[LogicalPlan] {
       }
     }
 
+    stripColumnReferenceMetadataInPlan(plan)
+  }
+
+  private def stripColumnReferenceMetadataInPlan(plan: LogicalPlan): LogicalPlan = {
     plan.transformExpressions {
       case a: AttributeReference if isColumnReference(a) =>
         // Remove the special metadata from this `AttributeReference`, as the detection is done.

sql/core/src/test/scala/org/apache/spark/sql/DataFrameSelfJoinSuite.scala

@@ -17,6 +17,7 @@
 
 package org.apache.spark.sql
 
+import org.apache.spark.sql.expressions.Window
 import org.apache.spark.sql.functions.{count, sum}
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SharedSparkSession
@@ -202,4 +203,15 @@ class DataFrameSelfJoinSuite extends QueryTest with SharedSparkSession {
       assertAmbiguousSelfJoin(df1.join(df4).join(df2).select(df2("id")))
     }
   }
+
+  test("SPARK-28344: don't fail as ambiguous self join when there is no join") {
+    withSQLConf(
+      SQLConf.FAIL_AMBIGUOUS_SELF_JOIN_ENABLED.key -> "true") {
+      val df = Seq(1, 1, 2, 2).toDF("a")
+      val w = Window.partitionBy(df("a"))
+      checkAnswer(
+        df.select(df("a").alias("x"), sum(df("a")).over(w)),
+        Seq((1, 2), (1, 2), (2, 4), (2, 4)).map(Row.fromTuple))
+    }
+  }
 }