diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
index 6de17e5924d04..a5102b1018a8e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
@@ -1510,12 +1510,13 @@ class DataFrame private[sql](
   }
 
   private def collect(needCallback: Boolean): Array[Row] = {
-    def execute(): Array[Row] = withNewExecutionId {
-      queryExecution.executedPlan.executeCollectPublic()
+    val dfToExecute = withPlan(ReturnAnswer(logicalPlan))
+    def execute(): Array[Row] = dfToExecute.withNewExecutionId {
+      dfToExecute.queryExecution.executedPlan.executeCollectPublic()
     }
 
     if (needCallback) {
-      withCallback("collect", this)(_ => execute())
+      withCallback("collect", dfToExecute)(_ => execute())
     } else {
       execute()
     }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala
index 8616fe317034f..8e9f1d6aaaff8 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala
@@ -44,7 +44,7 @@ class QueryExecution(val sqlContext: SQLContext, val logical: LogicalPlan) {
 
   lazy val sparkPlan: SparkPlan = {
     SQLContext.setActive(sqlContext)
-    sqlContext.planner.plan(ReturnAnswer(optimizedPlan)).next()
+    sqlContext.planner.plan(optimizedPlan).next()
   }
 
   // executedPlan should not be used to initialize any SparkPlan. It should be
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/limit.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/limit.scala
index 5acde5996b543..615a5a94445ec 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/limit.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/limit.scala
@@ -27,13 +27,15 @@ import org.apache.spark.sql.catalyst.plans.physical._
  * Take the first `limit` elements and collect them to a single partition.
  *
  * This operator will be used when a logical `Limit` operation is the final operator in an
- * logical plan, which happens when the user is collecting results back to the driver.
+ * logical plan and the user is collecting results back to the driver.
  */
 case class CollectLimit(limit: Int, child: SparkPlan) extends UnaryNode {
   override def output: Seq[Attribute] = child.output
   override def outputPartitioning: Partitioning = SinglePartition
   override def executeCollect(): Array[InternalRow] = child.executeTake(limit)
-  protected override def doExecute(): RDD[InternalRow] = sparkContext.makeRDD(executeCollect(), 1)
+  protected override def doExecute(): RDD[InternalRow] = {
+    throw new UnsupportedOperationException("doExecute() should not be called on CollectLimit()")
+  }
 }
 
 /**
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
index 2ff1bfaf95153..f62f8a2df81ba 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
@@ -182,12 +182,6 @@ class PlannerSuite extends SharedSQLContext {
     }
   }
 
-  test("terminal limits use CollectLimit") {
-    val query = testData.select('value).limit(2)
-    val planned = query.queryExecution.sparkPlan
-    assert(planned.isInstanceOf[CollectLimit])
-  }
-
   test("PartitioningCollection") {
     withTempTable("normal", "small", "tiny") {
       testData.registerTempTable("normal")