Treat checkpoint as an RDD operation

core/src/main/scala/org/apache/spark/rdd/RDD.scala

@@ -285,6 +285,16 @@ abstract class RDD[T: ClassTag](
    */
   private[spark] def withScope[U](body: => U): U = RDDOperationScope.withScope[U](sc)(body)
 
+  /**
+   * Execute a block of code in a scope such that all new RDDs created in this body will
+   * be part of the same scope. For more detail, see {{org.apache.spark.rdd.RDDOperationScope}}.
+   *
+   * Note: Return statements are NOT allowed in the given body.
+   */
+  private[spark] def withNamedScope[U](scopeName: String)(body: => U): U = {
+    RDDOperationScope.withScope[U](sc)(body)
+  }
+
   // Transformations (return a new RDD)
 
   /**
@@ -1512,7 +1522,7 @@ abstract class RDD[T: ClassTag](
    * has completed (therefore the RDD has been materialized and potentially stored in memory).
    * doCheckpoint() is called recursively on the parent RDDs.
    */
-  private[spark] def doCheckpoint() {
+  private[spark] def doCheckpoint(): Unit = withNamedScope("checkpoint") {
     if (!doCheckpointCalled) {
       doCheckpointCalled = true
       if (checkpointData.isDefined) {