init

Author: richardc-db

sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala

@@ -319,3 +319,51 @@ case class RDDScanExec(
 
   override def getStream: Option[SparkDataStream] = stream
 }
+
+/**
+ * A special case of RDDScanExec that is used to represent a scan without a `FROM` clause.
+ * For example, 'select version()'.
+ *
+ * We do not extend `RDDScanExec` in order to avoid complexity due to `TreeNode.makeCopy` and
+ * `TreeNode`'s general use of reflection.
+ */
+case class OneRowRelationExec() extends LeafExecNode
+  with StreamSourceAwareSparkPlan
+  with InputRDDCodegen {
+
+  override val nodeName: String = s"Scan OneRowRelation"
+
+  override val output: Seq[Attribute] = Nil
+
+  val rdd = session.sparkContext.parallelize(Seq(InternalRow()), 1)
+
+  override lazy val metrics = Map(
+    "numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output rows"))
+
+  protected override def doExecute(): RDD[InternalRow] = {
+    val numOutputRows = longMetric("numOutputRows")
+    rdd.mapPartitionsWithIndexInternal { (index, iter) =>
+      val proj = UnsafeProjection.create(schema)
+      proj.initialize(index)
+      iter.map { r =>
+        numOutputRows += 1
+        proj(r)
+      }
+    }
+  }
+
+  override def simpleString(maxFields: Int): String = {
+    s"$nodeName${truncatedString(output, "[", ",", "]", maxFields)}"
+  }
+
+  override def inputRDD: RDD[InternalRow] = rdd
+
+  // Input can be InternalRow, has to be turned into UnsafeRows.
+  override protected val createUnsafeProjection: Boolean = true
+
+  override protected def doCanonicalize(): SparkPlan = {
+    super.doCanonicalize().asInstanceOf[OneRowRelationExec].copy()
+  }
+
+  override def getStream: Option[SparkDataStream] = None
+}

sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala

@@ -690,8 +690,6 @@ abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
     }
   }
 
-  protected lazy val singleRowRdd = session.sparkContext.parallelize(Seq(InternalRow()), 1)
-
   object InMemoryScans extends Strategy {
     def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
       case PhysicalOperation(projectList, filters, mem: InMemoryRelation) =>
@@ -1040,7 +1038,7 @@ abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
           generator, g.requiredChildOutput, outer,
           g.qualifiedGeneratorOutput, planLater(child)) :: Nil
       case _: logical.OneRowRelation =>
-        execution.RDDScanExec(Nil, singleRowRdd, "OneRowRelation") :: Nil
+        execution.OneRowRelationExec() :: Nil
       case r: logical.Range =>
         execution.RangeExec(r) :: Nil
       case r: logical.RepartitionByExpression =>

sql/core/src/main/scala/org/apache/spark/sql/execution/WholeStageCodegenExec.scala

@@ -56,6 +56,7 @@ trait CodegenSupport extends SparkPlan {
     case _: SortMergeJoinExec => "smj"
     case _: BroadcastNestedLoopJoinExec => "bnlj"
     case _: RDDScanExec => "rdd"
+    case _: OneRowRelationExec => "orr"
     case _: DataSourceScanExec => "scan"
     case _: InMemoryTableScanExec => "memoryScan"
     case _: WholeStageCodegenExec => "wholestagecodegen"

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

@@ -38,7 +38,7 @@ import org.apache.spark.sql.catalyst.optimizer.{ConvertToLocalRelation, NestedCo
 import org.apache.spark.sql.catalyst.parser.ParseException
 import org.apache.spark.sql.catalyst.plans.logical.{LocalLimit, Project, RepartitionByExpression, Sort}
 import org.apache.spark.sql.connector.catalog.CatalogManager.SESSION_CATALOG_NAME
-import org.apache.spark.sql.execution.{CommandResultExec, UnionExec}
+import org.apache.spark.sql.execution.{CommandResultExec, OneRowRelationExec, UnionExec}
 import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
 import org.apache.spark.sql.execution.aggregate._
 import org.apache.spark.sql.execution.columnar.InMemoryTableScanExec
@@ -4962,6 +4962,18 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
       parameters = Map("plan" -> "'Aggregate [groupingsets(Vector(0), posexplode(array(col)))]")
     )
   }
+
+  Seq(true, false).foreach { codegenEnabled =>
+    test(s"SPARK-52060: one row relation with codegen enabled - $codegenEnabled") {
+      withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> codegenEnabled.toString) {
+        val df = spark.sql("select 'test' stringCol")
+        checkAnswer(df, Row("test"))
+        val plan = df.queryExecution.executedPlan
+        val oneRowRelationExists = plan.find(_.isInstanceOf[OneRowRelationExec]).isDefined
+        assert(oneRowRelationExists)
+      }
+    }
+  }
 }
 
 case class Foo(bar: Option[String])