Revert "[SPARK-13031] [SQL] cleanup codegen and improve test coverage"

This reverts commit cc18a71992.

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala

@@ -144,23 +144,14 @@ class CodegenContext {
 
   private val curId = new java.util.concurrent.atomic.AtomicInteger()
 
-  /**
-    * A prefix used to generate fresh name.
-    */
-  var freshNamePrefix = ""
-
   /**
    * Returns a term name that is unique within this instance of a `CodeGenerator`.
    *
    * (Since we aren't in a macro context we do not seem to have access to the built in `freshName`
    * function.)
    */
-  def freshName(name: String): String = {
+  def freshName(prefix: String): String = {
-    if (freshNamePrefix == "") {
+    s"$prefix${curId.getAndIncrement}"
-      s"$name${curId.getAndIncrement}"
-    } else {
-      s"${freshNamePrefix}_$name${curId.getAndIncrement}"
-    }
   }
 
   /**

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateMutableProjection.scala

@@ -93,7 +93,7 @@ object GenerateMutableProjection extends CodeGenerator[Seq[Expression], () => Mu
             // Can't call setNullAt on DecimalType, because we need to keep the offset
             s"""
               if (this.isNull_$i) {
-                ${ctx.setColumn("mutableRow", e.dataType, i, "null")};
+                ${ctx.setColumn("mutableRow", e.dataType, i, null)};
               } else {
                 ${ctx.setColumn("mutableRow", e.dataType, i, s"this.value_$i")};
               }

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

@@ -22,11 +22,9 @@ import scala.collection.mutable.ArrayBuffer
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.SQLContext
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.{Attribute, BoundReference, Expression, LeafExpression}
 import org.apache.spark.sql.catalyst.expressions.codegen._
-import org.apache.spark.sql.catalyst.plans.physical.Partitioning
 import org.apache.spark.sql.catalyst.rules.Rule
-import org.apache.spark.util.Utils
 
 /**
   * An interface for those physical operators that support codegen.
@@ -44,16 +42,10 @@ trait CodegenSupport extends SparkPlan {
   private var parent: CodegenSupport = null
 
   /**
-    * Returns the RDD of InternalRow which generates the input rows.
+    * Returns an input RDD of InternalRow and Java source code to process them.
     */
-  def upstream(): RDD[InternalRow]
+  def produce(ctx: CodegenContext, parent: CodegenSupport): (RDD[InternalRow], String) = {
-
-  /**
-    * Returns Java source code to process the rows from upstream.
-    */
-  def produce(ctx: CodegenContext, parent: CodegenSupport): String = {
     this.parent = parent
-    ctx.freshNamePrefix = nodeName
     doProduce(ctx)
   }
 
@@ -74,41 +66,16 @@ trait CodegenSupport extends SparkPlan {
     *     # call consume(), wich will call parent.doConsume()
     *   }
     */
-  protected def doProduce(ctx: CodegenContext): String
+  protected def doProduce(ctx: CodegenContext): (RDD[InternalRow], String)
 
   /**
-    * Consume the columns generated from current SparkPlan, call it's parent.
+    * Consume the columns generated from current SparkPlan, call it's parent or create an iterator.
     */
-  def consume(ctx: CodegenContext, input: Seq[ExprCode], row: String = null): String = {
+  protected def consume(ctx: CodegenContext, columns: Seq[ExprCode]): String = {
-    if (input != null) {
+    assert(columns.length == output.length)
-      assert(input.length == output.length)
+    parent.doConsume(ctx, this, columns)
-    }
-    parent.consumeChild(ctx, this, input, row)
   }
 
-  /**
-    * Consume the columns generated from it's child, call doConsume() or emit the rows.
-    */
-  def consumeChild(
-      ctx: CodegenContext,
-      child: SparkPlan,
-      input: Seq[ExprCode],
-      row: String = null): String = {
-    ctx.freshNamePrefix = nodeName
-    if (row != null) {
-      ctx.currentVars = null
-      ctx.INPUT_ROW = row
-      val evals = child.output.zipWithIndex.map { case (attr, i) =>
-        BoundReference(i, attr.dataType, attr.nullable).gen(ctx)
-      }
-      s"""
-         | ${evals.map(_.code).mkString("\n")}
-         | ${doConsume(ctx, evals)}
-       """.stripMargin
-    } else {
-      doConsume(ctx, input)
-    }
-  }
 
   /**
     * Generate the Java source code to process the rows from child SparkPlan.
@@ -122,9 +89,7 @@ trait CodegenSupport extends SparkPlan {
     *     # call consume(), which will call parent.doConsume()
     *   }
     */
-  protected def doConsume(ctx: CodegenContext, input: Seq[ExprCode]): String = {
+  def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String
-    throw new UnsupportedOperationException
-  }
 }
 
 
@@ -137,36 +102,31 @@ trait CodegenSupport extends SparkPlan {
 case class InputAdapter(child: SparkPlan) extends LeafNode with CodegenSupport {
 
   override def output: Seq[Attribute] = child.output
-  override def outputPartitioning: Partitioning = child.outputPartitioning
-  override def outputOrdering: Seq[SortOrder] = child.outputOrdering
 
-  override def doPrepare(): Unit = {
+  override def supportCodegen: Boolean = true
-    child.prepare()
-  }
 
-  override def doExecute(): RDD[InternalRow] = {
+  override def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) = {
-    child.execute()
-  }
-
-  override def supportCodegen: Boolean = false
-
-  override def upstream(): RDD[InternalRow] = {
-    child.execute()
-  }
-
-  override def doProduce(ctx: CodegenContext): String = {
     val exprs = output.zipWithIndex.map(x => new BoundReference(x._2, x._1.dataType, true))
     val row = ctx.freshName("row")
     ctx.INPUT_ROW = row
     ctx.currentVars = null
     val columns = exprs.map(_.gen(ctx))
-    s"""
+    val code = s"""
        |  while (input.hasNext()) {
        |   InternalRow $row = (InternalRow) input.next();
        |   ${columns.map(_.code).mkString("\n")}
        |   ${consume(ctx, columns)}
        | }
      """.stripMargin
+    (child.execute(), code)
+  }
+
+  def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String = {
+    throw new UnsupportedOperationException
+  }
+
+  override def doExecute(): RDD[InternalRow] = {
+    throw new UnsupportedOperationException
   }
 
   override def simpleString: String = "INPUT"
@@ -183,20 +143,16 @@ case class InputAdapter(child: SparkPlan) extends LeafNode with CodegenSupport {
   *
   * -> execute()
   *     |
-  *  doExecute() --------->   upstream() -------> upstream() ------> execute()
+  *  doExecute() -------->   produce()
-  *     |
-  *      ----------------->   produce()
   *                             |
   *                          doProduce()  -------> produce()
   *                                                   |
-  *                                                doProduce()
+  *                                                doProduce() ---> execute()
   *                                                   |
   *                                                consume()
-  *                        consumeChild() <-----------|
+  *                          doConsume()  ------------|
   *                             |
-  *                          doConsume()
+  *  doConsume()  <-----    consume()
-  *                             |
-  *  consumeChild()  <-----  consume()
   *
   * SparkPlan A should override doProduce() and doConsume().
   *
@@ -206,19 +162,11 @@ case class InputAdapter(child: SparkPlan) extends LeafNode with CodegenSupport {
 case class WholeStageCodegen(plan: CodegenSupport, children: Seq[SparkPlan])
   extends SparkPlan with CodegenSupport {
 
-  override def supportCodegen: Boolean = false
-
   override def output: Seq[Attribute] = plan.output
-  override def outputPartitioning: Partitioning = plan.outputPartitioning
-  override def outputOrdering: Seq[SortOrder] = plan.outputOrdering
-
-  override def doPrepare(): Unit = {
-    plan.prepare()
-  }
 
   override def doExecute(): RDD[InternalRow] = {
     val ctx = new CodegenContext
-    val code = plan.produce(ctx, this)
+    val (rdd, code) = plan.produce(ctx, this)
     val references = ctx.references.toArray
     val source = s"""
       public Object generate(Object[] references) {
@@ -229,25 +177,22 @@ case class WholeStageCodegen(plan: CodegenSupport, children: Seq[SparkPlan])
 
        private Object[] references;
        ${ctx.declareMutableStates()}
-        ${ctx.declareAddedFunctions()}
 
        public GeneratedIterator(Object[] references) {
          this.references = references;
          ${ctx.initMutableStates()}
        }
 
-        protected void processNext() throws java.io.IOException {
+       protected void processNext() {
          $code
        }
       }
      """
-
     // try to compile, helpful for debug
     // println(s"${CodeFormatter.format(source)}")
     CodeGenerator.compile(source)
 
-    plan.upstream().mapPartitions { iter =>
+    rdd.mapPartitions { iter =>
-
       val clazz = CodeGenerator.compile(source)
       val buffer = clazz.generate(references).asInstanceOf[BufferedRowIterator]
       buffer.setInput(iter)
@@ -258,28 +203,11 @@ case class WholeStageCodegen(plan: CodegenSupport, children: Seq[SparkPlan])
     }
   }
 
-  override def upstream(): RDD[InternalRow] = {
+  override def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) = {
     throw new UnsupportedOperationException
   }
 
-  override def doProduce(ctx: CodegenContext): String = {
+  override def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String = {
-    throw new UnsupportedOperationException
-  }
-
-  override def consumeChild(
-      ctx: CodegenContext,
-      child: SparkPlan,
-      input: Seq[ExprCode],
-      row: String = null): String = {
-
-    if (row != null) {
-      // There is an UnsafeRow already
-      s"""
-         | currentRow = $row;
-         | return;
-       """.stripMargin
-    } else {
-      assert(input != null)
     if (input.nonEmpty) {
       val colExprs = output.zipWithIndex.map { case (attr, i) =>
         BoundReference(i, attr.dataType, attr.nullable)
@@ -300,7 +228,6 @@ case class WholeStageCodegen(plan: CodegenSupport, children: Seq[SparkPlan])
        """.stripMargin
     }
   }
-  }
 
   override def generateTreeString(
       depth: Int,
@@ -319,7 +246,7 @@ case class WholeStageCodegen(plan: CodegenSupport, children: Seq[SparkPlan])
     builder.append(simpleString)
     builder.append("\n")
 
-    plan.generateTreeString(depth + 2, lastChildren :+ false :+ true, builder)
+    plan.generateTreeString(depth + 1, lastChildren :+children.isEmpty :+ true, builder)
     if (children.nonEmpty) {
       children.init.foreach(_.generateTreeString(depth + 1, lastChildren :+ false, builder))
       children.last.generateTreeString(depth + 1, lastChildren :+ true, builder)
@@ -359,14 +286,13 @@ private[sql] case class CollapseCodegenStages(sqlContext: SQLContext) extends Ru
         case plan: CodegenSupport if supportCodegen(plan) &&
           // Whole stage codegen is only useful when there are at least two levels of operators that
           // support it (save at least one projection/iterator).
-          (Utils.isTesting || plan.children.exists(supportCodegen)) =>
+          plan.children.exists(supportCodegen) =>
 
           var inputs = ArrayBuffer[SparkPlan]()
           val combined = plan.transform {
             case p if !supportCodegen(p) =>
-              val input = apply(p)  // collapse them recursively
+              inputs += p
-              inputs += input
+              InputAdapter(p)
-              InputAdapter(input)
           }.asInstanceOf[CodegenSupport]
           WholeStageCodegen(combined, inputs)
       }

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregate.scala

@@ -117,7 +117,9 @@ case class TungstenAggregate(
   override def supportCodegen: Boolean = {
     groupingExpressions.isEmpty &&
       // ImperativeAggregate is not supported right now
-      !aggregateExpressions.exists(_.aggregateFunction.isInstanceOf[ImperativeAggregate])
+      !aggregateExpressions.exists(_.aggregateFunction.isInstanceOf[ImperativeAggregate]) &&
+      // final aggregation only have one row, do not need to codegen
+      !aggregateExpressions.exists(e => e.mode == Final || e.mode == Complete)
   }
 
   // The variables used as aggregation buffer
@@ -125,11 +127,7 @@ case class TungstenAggregate(
 
   private val modes = aggregateExpressions.map(_.mode).distinct
 
-  override def upstream(): RDD[InternalRow] = {
+  protected override def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) = {
-    child.asInstanceOf[CodegenSupport].upstream()
-  }
-
-  protected override def doProduce(ctx: CodegenContext): String = {
     val initAgg = ctx.freshName("initAgg")
     ctx.addMutableState("boolean", initAgg, s"$initAgg = false;")
 
@@ -139,80 +137,50 @@ case class TungstenAggregate(
     bufVars = initExpr.map { e =>
       val isNull = ctx.freshName("bufIsNull")
       val value = ctx.freshName("bufValue")
-      ctx.addMutableState("boolean", isNull, "")
-      ctx.addMutableState(ctx.javaType(e.dataType), value, "")
       // The initial expression should not access any column
       val ev = e.gen(ctx)
       val initVars = s"""
-         | $isNull = ${ev.isNull};
+         | boolean $isNull = ${ev.isNull};
-         | $value = ${ev.value};
+         | ${ctx.javaType(e.dataType)} $value = ${ev.value};
        """.stripMargin
       ExprCode(ev.code + initVars, isNull, value)
     }
 
-    // generate variables for output
+    val (rdd, childSource) = child.asInstanceOf[CodegenSupport].produce(ctx, this)
-    val (resultVars, genResult) = if (modes.contains(Final) | modes.contains(Complete)) {
+    val source =
-      // evaluate aggregate results
-      ctx.currentVars = bufVars
-      val bufferAttrs = functions.flatMap(_.aggBufferAttributes)
-      val aggResults = functions.map(_.evaluateExpression).map { e =>
-        BindReferences.bindReference(e, bufferAttrs).gen(ctx)
-      }
-      // evaluate result expressions
-      ctx.currentVars = aggResults
-      val resultVars = resultExpressions.map { e =>
-        BindReferences.bindReference(e, aggregateAttributes).gen(ctx)
-      }
-      (resultVars, s"""
-        | ${aggResults.map(_.code).mkString("\n")}
-        | ${resultVars.map(_.code).mkString("\n")}
-       """.stripMargin)
-    } else {
-      // output the aggregate buffer directly
-      (bufVars, "")
-    }
-
-    val doAgg = ctx.freshName("doAgg")
-    ctx.addNewFunction(doAgg,
-      s"""
-         | private void $doAgg() {
-         |   // initialize aggregation buffer
-         |   ${bufVars.map(_.code).mkString("\n")}
-         |
-         |   ${child.asInstanceOf[CodegenSupport].produce(ctx, this)}
-         | }
-       """.stripMargin)
-
       s"""
          | if (!$initAgg) {
          |   $initAgg = true;
-       |   $doAgg();
+         |
+         |   // initialize aggregation buffer
+         |   ${bufVars.map(_.code).mkString("\n")}
+         |
+         |   $childSource
          |
          |   // output the result
-       |   $genResult
+         |   ${consume(ctx, bufVars)}
-       |
-       |   ${consume(ctx, resultVars)}
          | }
        """.stripMargin
+
+    (rdd, source)
   }
 
-  override def doConsume(ctx: CodegenContext, input: Seq[ExprCode]): String = {
+  override def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String = {
     // only have DeclarativeAggregate
     val functions = aggregateExpressions.map(_.aggregateFunction.asInstanceOf[DeclarativeAggregate])
-    val inputAttrs = functions.flatMap(_.aggBufferAttributes) ++ child.output
+    // the mode could be only Partial or PartialMerge
-    val updateExpr = aggregateExpressions.flatMap { e =>
+    val updateExpr = if (modes.contains(Partial)) {
-      e.mode match {
+      functions.flatMap(_.updateExpressions)
-        case Partial | Complete =>
+    } else {
-          e.aggregateFunction.asInstanceOf[DeclarativeAggregate].updateExpressions
+      functions.flatMap(_.mergeExpressions)
-        case PartialMerge | Final =>
-          e.aggregateFunction.asInstanceOf[DeclarativeAggregate].mergeExpressions
-      }
     }
 
+    val inputAttr = functions.flatMap(_.aggBufferAttributes) ++ child.output
+    val boundExpr = updateExpr.map(e => BindReferences.bindReference(e, inputAttr))
     ctx.currentVars = bufVars ++ input
     // TODO: support subexpression elimination
-    val updates = updateExpr.zipWithIndex.map { case (e, i) =>
+    val codes = boundExpr.zipWithIndex.map { case (e, i) =>
-      val ev = BindReferences.bindReference[Expression](e, inputAttrs).gen(ctx)
+      val ev = e.gen(ctx)
       s"""
          | ${ev.code}
          | ${bufVars(i).isNull} = ${ev.isNull};
@@ -222,7 +190,7 @@ case class TungstenAggregate(
 
     s"""
        | // do aggregate and update aggregation buffer
-       | ${updates.mkString("")}
+       | ${codes.mkString("")}
      """.stripMargin
   }
 

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

@@ -37,15 +37,11 @@ case class Project(projectList: Seq[NamedExpression], child: SparkPlan)
 
   override def output: Seq[Attribute] = projectList.map(_.toAttribute)
 
-  override def upstream(): RDD[InternalRow] = {
+  protected override def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) = {
-    child.asInstanceOf[CodegenSupport].upstream()
-  }
-
-  protected override def doProduce(ctx: CodegenContext): String = {
     child.asInstanceOf[CodegenSupport].produce(ctx, this)
   }
 
-  override def doConsume(ctx: CodegenContext, input: Seq[ExprCode]): String = {
+  override def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String = {
     val exprs = projectList.map(x =>
       ExpressionCanonicalizer.execute(BindReferences.bindReference(x, child.output)))
     ctx.currentVars = input
@@ -80,15 +76,11 @@ case class Filter(condition: Expression, child: SparkPlan) extends UnaryNode wit
     "numInputRows" -> SQLMetrics.createLongMetric(sparkContext, "number of input rows"),
     "numOutputRows" -> SQLMetrics.createLongMetric(sparkContext, "number of output rows"))
 
-  override def upstream(): RDD[InternalRow] = {
+  protected override def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) = {
-    child.asInstanceOf[CodegenSupport].upstream()
-  }
-
-  protected override def doProduce(ctx: CodegenContext): String = {
     child.asInstanceOf[CodegenSupport].produce(ctx, this)
   }
 
-  override def doConsume(ctx: CodegenContext, input: Seq[ExprCode]): String = {
+  override def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String = {
     val expr = ExpressionCanonicalizer.execute(
       BindReferences.bindReference(condition, child.output))
     ctx.currentVars = input
@@ -161,21 +153,17 @@ case class Range(
     output: Seq[Attribute])
   extends LeafNode with CodegenSupport {
 
-  override def upstream(): RDD[InternalRow] = {
+  protected override def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) = {
-    sqlContext.sparkContext.parallelize(0 until numSlices, numSlices).map(i => InternalRow(i))
+    val initTerm = ctx.freshName("range_initRange")
-  }
-
-  protected override def doProduce(ctx: CodegenContext): String = {
-    val initTerm = ctx.freshName("initRange")
     ctx.addMutableState("boolean", initTerm, s"$initTerm = false;")
-    val partitionEnd = ctx.freshName("partitionEnd")
+    val partitionEnd = ctx.freshName("range_partitionEnd")
     ctx.addMutableState("long", partitionEnd, s"$partitionEnd = 0L;")
-    val number = ctx.freshName("number")
+    val number = ctx.freshName("range_number")
     ctx.addMutableState("long", number, s"$number = 0L;")
-    val overflow = ctx.freshName("overflow")
+    val overflow = ctx.freshName("range_overflow")
     ctx.addMutableState("boolean", overflow, s"$overflow = false;")
 
-    val value = ctx.freshName("value")
+    val value = ctx.freshName("range_value")
     val ev = ExprCode("", "false", value)
     val BigInt = classOf[java.math.BigInteger].getName
     val checkEnd = if (step > 0) {
@@ -184,10 +172,15 @@ case class Range(
       s"$number > $partitionEnd"
     }
 
-    ctx.addNewFunction("initRange",
+    val rdd = sqlContext.sparkContext.parallelize(0 until numSlices, numSlices)
-      s"""
+      .map(i => InternalRow(i))
-        | private void initRange(int idx) {
+
-        |   $BigInt index = $BigInt.valueOf(idx);
+    val code = s"""
+      | // initialize Range
+      | if (!$initTerm) {
+      |   $initTerm = true;
+      |   if (input.hasNext()) {
+      |     $BigInt index = $BigInt.valueOf(((InternalRow) input.next()).getInt(0));
       |     $BigInt numSlice = $BigInt.valueOf(${numSlices}L);
       |     $BigInt numElement = $BigInt.valueOf(${numElements.toLong}L);
       |     $BigInt step = $BigInt.valueOf(${step}L);
@@ -211,15 +204,6 @@ case class Range(
       |     } else {
       |       $partitionEnd = end.longValue();
       |     }
-        | }
-       """.stripMargin)
-
-    s"""
-      | // initialize Range
-      | if (!$initTerm) {
-      |   $initTerm = true;
-      |   if (input.hasNext()) {
-      |     initRange(((InternalRow) input.next()).getInt(0));
       |   } else {
       |     return;
       |   }
@@ -234,6 +218,12 @@ case class Range(
       |  ${consume(ctx, Seq(ev))}
       | }
      """.stripMargin
+
+    (rdd, code)
+  }
+
+  def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String = {
+    throw new UnsupportedOperationException
   }
 
   protected override def doExecute(): RDD[InternalRow] = {

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

@@ -1939,8 +1939,6 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
   }
 
   test("Common subexpression elimination") {
-    // TODO: support subexpression elimination in whole stage codegen
-    withSQLConf("spark.sql.codegen.wholeStage" -> "false") {
     // select from a table to prevent constant folding.
     val df = sql("SELECT a, b from testData2 limit 1")
     checkAnswer(df, Row(1, 1))
@@ -1994,7 +1992,6 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
     sqlContext.setConf("spark.sql.subexpressionElimination.enabled", "true")
     verifyCallCount(df.selectExpr("testUdf(a)", "testUdf(a)"), Row(1, 1), 1)
   }
-  }
 
   test("SPARK-10707: nullability should be correctly propagated through set operations (1)") {
     // This test produced an incorrect result of 1 before the SPARK-10707 fix because of the

sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsSuite.scala

@@ -335,7 +335,6 @@ class SQLMetricsSuite extends SparkFunSuite with SharedSQLContext {
 
   test("save metrics") {
     withTempPath { file =>
-      withSQLConf("spark.sql.codegen.wholeStage" -> "false") {
       val previousExecutionIds = sqlContext.listener.executionIdToData.keySet
       // Assume the execution plan is
       // PhysicalRDD(nodeId = 0)
@@ -354,7 +353,6 @@ class SQLMetricsSuite extends SparkFunSuite with SharedSQLContext {
       assert(metricValues.values.toSeq === Seq("2"))
     }
   }
-  }
 
 }
 

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

@@ -199,7 +199,7 @@ private[sql] trait SQLTestUtils
     val schema = df.schema
     val childRDD = df
       .queryExecution
-      .sparkPlan.asInstanceOf[org.apache.spark.sql.execution.Filter]
+      .executedPlan.asInstanceOf[org.apache.spark.sql.execution.Filter]
       .child
       .execute()
       .map(row => Row.fromSeq(row.copy().toSeq(schema)))

sql/core/src/test/scala/org/apache/spark/sql/util/DataFrameCallbackSuite.scala

@@ -97,12 +97,10 @@ class DataFrameCallbackSuite extends QueryTest with SharedSQLContext {
     }
     sqlContext.listenerManager.register(listener)
 
-    withSQLConf("spark.sql.codegen.wholeStage" -> "false") {
     val df = Seq(1 -> "a").toDF("i", "j").groupBy("i").count()
     df.collect()
     df.collect()
     Seq(1 -> "a", 2 -> "a").toDF("i", "j").groupBy("i").count().collect()
-    }
 
     assert(metrics.length == 3)
     assert(metrics(0) == 1)