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From: rxin@apache.org
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Message-Id: <34db49f446f94176a35062531a33c2db@git.apache.org>
Subject: spark git commit: [SPARK-15856][SQL] Revert API breaking changes made
 in SQLContext.range
Date: Sat, 11 Jun 2016 22:28:42 +0000 (UTC)
archived-at: Sat, 11 Jun 2016 22:28:44 -0000

Repository: spark
Updated Branches:
  refs/heads/master 5bb4564cd -> 75705e8db


[SPARK-15856][SQL] Revert API breaking changes made in SQLContext.range

## What changes were proposed in this pull request?

It's easy for users to call `range(...).as[Long]` to get typed Dataset, and don't worth an API breaking change. This PR reverts it.

## How was this patch tested?

N/A

Author: Wenchen Fan <wenchen@databricks.com>

Closes #13605 from cloud-fan/range.


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/75705e8d
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/75705e8d
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/75705e8d

Branch: refs/heads/master
Commit: 75705e8dbb51ac91ffc7012fa67f072494c13832
Parents: 5bb4564
Author: Wenchen Fan <wenchen@databricks.com>
Authored: Sat Jun 11 15:28:40 2016 -0700
Committer: Reynold Xin <rxin@databricks.com>
Committed: Sat Jun 11 15:28:40 2016 -0700

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 .../scala/org/apache/spark/sql/SQLContext.scala | 36 ++++++++++----------
 1 file changed, 18 insertions(+), 18 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/75705e8d/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
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diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
index 23f2b6e..6fcc9bb 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
@@ -609,51 +609,51 @@ class SQLContext private[sql](val sparkSession: SparkSession)
 
   /**
    * :: Experimental ::
-   * Creates a [[Dataset]] with a single [[LongType]] column named `id`, containing elements
+   * Creates a [[DataFrame]] with a single [[LongType]] column named `id`, containing elements
    * in a range from 0 to `end` (exclusive) with step value 1.
    *
-   * @since 2.0.0
-   * @group dataset
+   * @since 1.4.1
+   * @group dataframe
    */
   @Experimental
-  def range(end: Long): Dataset[java.lang.Long] = sparkSession.range(end)
+  def range(end: Long): DataFrame = sparkSession.range(end).toDF()
 
   /**
    * :: Experimental ::
-   * Creates a [[Dataset]] with a single [[LongType]] column named `id`, containing elements
+   * Creates a [[DataFrame]] with a single [[LongType]] column named `id`, containing elements
    * in a range from `start` to `end` (exclusive) with step value 1.
    *
-   * @since 2.0.0
-   * @group dataset
+   * @since 1.4.0
+   * @group dataframe
    */
   @Experimental
-  def range(start: Long, end: Long): Dataset[java.lang.Long] = sparkSession.range(start, end)
+  def range(start: Long, end: Long): DataFrame = sparkSession.range(start, end).toDF()
 
   /**
    * :: Experimental ::
-   * Creates a [[Dataset]] with a single [[LongType]] column named `id`, containing elements
+   * Creates a [[DataFrame]] with a single [[LongType]] column named `id`, containing elements
    * in a range from `start` to `end` (exclusive) with a step value.
    *
    * @since 2.0.0
-   * @group dataset
+   * @group dataframe
    */
   @Experimental
-  def range(start: Long, end: Long, step: Long): Dataset[java.lang.Long] = {
-    sparkSession.range(start, end, step)
+  def range(start: Long, end: Long, step: Long): DataFrame = {
+    sparkSession.range(start, end, step).toDF()
   }
 
   /**
    * :: Experimental ::
-   * Creates a [[Dataset]] with a single [[LongType]] column named `id`, containing elements
-   * in a range from `start` to `end` (exclusive) with a step value, with partition number
+   * Creates a [[DataFrame]] with a single [[LongType]] column named `id`, containing elements
+   * in an range from `start` to `end` (exclusive) with an step value, with partition number
    * specified.
    *
-   * @since 2.0.0
-   * @group dataset
+   * @since 1.4.0
+   * @group dataframe
    */
   @Experimental
-  def range(start: Long, end: Long, step: Long, numPartitions: Int): Dataset[java.lang.Long] = {
-    sparkSession.range(start, end, step, numPartitions)
+  def range(start: Long, end: Long, step: Long, numPartitions: Int): DataFrame = {
+    sparkSession.range(start, end, step, numPartitions).toDF()
   }
 
   /**


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