[SPARK-40429][SQL] Only set KeyGroupedPartitioning when the referenced column is in the output

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2ScanPartitioningAndOrdering.scala

@@ -41,8 +41,18 @@ object V2ScanPartitioningAndOrdering extends Rule[LogicalPlan] with SQLConfHelpe
   private def partitioning(plan: LogicalPlan) = plan.transformDown {
     case d @ DataSourceV2ScanRelation(relation, scan: SupportsReportPartitioning, _, None, _) =>
       val catalystPartitioning = scan.outputPartitioning() match {
-        case kgp: KeyGroupedPartitioning => sequenceToOption(kgp.keys().map(
-          V2ExpressionUtils.toCatalystOpt(_, relation, relation.funCatalog)))
+        case kgp: KeyGroupedPartitioning =>
+          val partitioning = sequenceToOption(
+            kgp.keys().map(V2ExpressionUtils.toCatalystOpt(_, relation, relation.funCatalog)))
+          if (partitioning.isEmpty) {
+            None
+          } else {
+            if (partitioning.get.forall(p => p.references.subsetOf(d.outputSet))) {
+              partitioning
+            } else {
+              None
+            }
+          }
         case _: UnknownPartitioning => None
         case p => throw new IllegalArgumentException("Unsupported data source V2 partitioning " +
             "type: " + p.getClass.getSimpleName)

sql/core/src/test/scala/org/apache/spark/sql/connector/MetadataColumnSuite.scala

@@ -216,4 +216,20 @@ class MetadataColumnSuite extends DatasourceV2SQLBase {
       .withColumn("right_all", struct($"right.*"))
     checkAnswer(dfQuery, Row(1, "a", "b", Row(1, "a"), Row(1, "b")))
   }
+
+  test("SPARK-40429: Only set KeyGroupedPartitioning when the referenced column is in the output") {
+    withTable(tbl) {
+      sql(s"CREATE TABLE $tbl (id bigint, data string) PARTITIONED BY (id)")
+      sql(s"INSERT INTO $tbl VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+      checkAnswer(
+        spark.table(tbl).select("index", "_partition"),
+        Seq(Row(0, "3"), Row(0, "2"), Row(0, "1"))
+      )
+
+      checkAnswer(
+        spark.table(tbl).select("id", "index", "_partition"),
+        Seq(Row(3, 0, "3"), Row(2, 0, "2"), Row(1, 0, "1"))
+      )
+    }
+  }
 }