[SPARK-13457][SQL] Removes DataFrame RDD operations

## What changes were proposed in this pull request?

This PR removes DataFrame RDD operations. Original calls are now replaced by calls to methods of `DataFrame.rdd`.

## How was the this patch tested?

No extra tests are added. Existing tests should do the work.

Author: Cheng Lian <lian@databricks.com>

Closes #11323 from liancheng/remove-df-rdd-ops.

12 files changed, 15 insertions, 53 deletions

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 abb8fe552b..be902d688e 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
@@ -1427,48 +1427,6 @@ class DataFrame private[sql](
   def transform[U](t: DataFrame => DataFrame): DataFrame = t(this)
 
   /**
-   * Returns a new RDD by applying a function to all rows of this DataFrame.
-   * @group rdd
-   * @since 1.3.0
-   */
-  def map[R: ClassTag](f: Row => R): RDD[R] = rdd.map(f)
-
-  /**
-   * Returns a new RDD by first applying a function to all rows of this [[DataFrame]],
-   * and then flattening the results.
-   * @group rdd
-   * @since 1.3.0
-   */
-  def flatMap[R: ClassTag](f: Row => TraversableOnce[R]): RDD[R] = rdd.flatMap(f)
-
-  /**
-   * Returns a new RDD by applying a function to each partition of this DataFrame.
-   * @group rdd
-   * @since 1.3.0
-   */
-  def mapPartitions[R: ClassTag](f: Iterator[Row] => Iterator[R]): RDD[R] = {
-    rdd.mapPartitions(f)
-  }
-
-  /**
-   * Applies a function `f` to all rows.
-   * @group rdd
-   * @since 1.3.0
-   */
-  def foreach(f: Row => Unit): Unit = withNewExecutionId {
-    rdd.foreach(f)
-  }
-
-  /**
-   * Applies a function f to each partition of this [[DataFrame]].
-   * @group rdd
-   * @since 1.3.0
-   */
-  def foreachPartition(f: Iterator[Row] => Unit): Unit = withNewExecutionId {
-    rdd.foreachPartition(f)
-  }
-
-  /**
    * Returns the first `n` rows in the [[DataFrame]].
    *
    * Running take requires moving data into the application's driver process, and doing so with
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
index f06d16116e..a7258d742a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
@@ -306,6 +306,7 @@ class GroupedData protected[sql](
     val values = df.select(pivotColumn)
       .distinct()
       .sort(pivotColumn)  // ensure that the output columns are in a consistent logical order
+      .rdd
       .map(_.get(0))
       .take(maxValues + 1)
       .toSeq
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
index d912aeb70d..68a251757c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
@@ -100,7 +100,7 @@ private[r] object SQLUtils {
   }
 
   def dfToRowRDD(df: DataFrame): JavaRDD[Array[Byte]] = {
-    df.map(r => rowToRBytes(r))
+    df.rdd.map(r => rowToRBytes(r))
   }
 
   private[this] def doConversion(data: Object, dataType: DataType): Object = {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
index e295722cac..d7111a6a1c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
@@ -276,7 +276,7 @@ object JdbcUtils extends Logging {
     val rddSchema = df.schema
     val getConnection: () => Connection = createConnectionFactory(url, properties)
     val batchSize = properties.getProperty("batchsize", "1000").toInt
-    df.foreachPartition { iterator =>
+    df.rdd.foreachPartition { iterator =>
       savePartition(getConnection, table, iterator, rddSchema, nullTypes, batchSize, dialect)
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
index f54bff9f18..7d96ef6fe0 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
@@ -257,7 +257,7 @@ class DataFrameAggregateSuite extends QueryTest with SharedSQLContext {
   }
 
   test("count") {
-    assert(testData2.count() === testData2.map(_ => 1).count())
+    assert(testData2.count() === testData2.rdd.map(_ => 1).count())
 
     checkAnswer(
       testData2.agg(count('a), sumDistinct('a)), // non-partial
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
index fbffe867e4..bd51154c58 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
@@ -101,7 +101,7 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
       (implicit df: DataFrame): Unit = {
     def checkBinaryAnswer(df: DataFrame, expected: Seq[Row]) = {
       assertResult(expected.map(_.getAs[Array[Byte]](0).mkString(",")).sorted) {
-        df.map(_.getAs[Array[Byte]](0).mkString(",")).collect().toSeq.sorted
+        df.rdd.map(_.getAs[Array[Byte]](0).mkString(",")).collect().toSeq.sorted
       }
     }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
index 3c74464d57..c85eeddc2c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
@@ -599,7 +599,7 @@ class ParquetIOSuite extends QueryTest with ParquetTest with SharedSQLContext {
   test("null and non-null strings") {
     // Create a dataset where the first values are NULL and then some non-null values. The
     // number of non-nulls needs to be bigger than the ParquetReader batch size.
-    val data = sqlContext.range(200).map { i =>
+    val data = sqlContext.range(200).rdd.map { i =>
       if (i.getLong(0) < 150) Row(None)
       else Row("a")
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLListenerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLListenerSuite.scala
index 085e4a49a5..39920d8cc6 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLListenerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLListenerSuite.scala
@@ -330,7 +330,7 @@ class SQLListenerSuite extends SparkFunSuite with SharedSQLContext {
     // listener should ignore the non SQL stage
     assert(sqlContext.listener.stageIdToStageMetrics.size == previousStageNumber)
 
-    sqlContext.sparkContext.parallelize(1 to 10).toDF().foreach(i => ())
+    sqlContext.sparkContext.parallelize(1 to 10).toDF().rdd.foreach(i => ())
     sqlContext.sparkContext.listenerBus.waitUntilEmpty(10000)
     // listener should save the SQL stage
     assert(sqlContext.listener.stageIdToStageMetrics.size == previousStageNumber + 1)
@@ -398,7 +398,7 @@ class SQLListenerMemoryLeakSuite extends SparkFunSuite {
           ).toDF()
           df.collect()
           try {
-            df.foreach(_ => throw new RuntimeException("Oops"))
+            df.rdd.foreach(_ => throw new RuntimeException("Oops"))
           } catch {
             case e: SparkException => // This is expected for a failed job
           }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
index f141a9bd0f..12a5542bd4 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
@@ -210,7 +210,7 @@ object SparkSubmitClassLoaderTest extends Logging {
     }
     // Second, we load classes at the executor side.
     logInfo("Testing load classes at the executor side.")
-    val result = df.mapPartitions { x =>
+    val result = df.rdd.mapPartitions { x =>
       var exception: String = null
       try {
         Utils.classForName(args(0))
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
index 3208ebc9ff..1002487447 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
@@ -664,11 +664,13 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter {
 
   test("implement identity function using case statement") {
     val actual = sql("SELECT (CASE key WHEN key THEN key END) FROM src")
+      .rdd
       .map { case Row(i: Int) => i }
       .collect()
       .toSet
 
     val expected = sql("SELECT key FROM src")
+      .rdd
       .map { case Row(i: Int) => i }
       .collect()
       .toSet
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala
index b11d1d9de0..68249517f5 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala
@@ -119,6 +119,7 @@ class OrcQuerySuite extends QueryTest with BeforeAndAfterAll with OrcTest {
       // expr = (not leaf-0)
       assertResult(10) {
         sql("SELECT name, contacts FROM t where age > 5")
+          .rdd
           .flatMap(_.getAs[Seq[_]]("contacts"))
           .count()
       }
@@ -131,7 +132,7 @@ class OrcQuerySuite extends QueryTest with BeforeAndAfterAll with OrcTest {
         val df = sql("SELECT name, contacts FROM t WHERE age > 5 AND age < 8")
         assert(df.count() === 2)
         assertResult(4) {
-          df.flatMap(_.getAs[Seq[_]]("contacts")).count()
+          df.rdd.flatMap(_.getAs[Seq[_]]("contacts")).count()
         }
       }
 
@@ -143,7 +144,7 @@ class OrcQuerySuite extends QueryTest with BeforeAndAfterAll with OrcTest {
         val df = sql("SELECT name, contacts FROM t WHERE age < 2 OR age > 8")
         assert(df.count() === 3)
         assertResult(6) {
-          df.flatMap(_.getAs[Seq[_]]("contacts")).count()
+          df.rdd.flatMap(_.getAs[Seq[_]]("contacts")).count()
         }
       }
     }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala
index 68d5c7da1f..a127cf6e4b 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala
@@ -854,7 +854,7 @@ abstract class ParquetPartitioningTest extends QueryTest with SQLTestUtils with
     test(s"hive udfs $table") {
       checkAnswer(
         sql(s"SELECT concat(stringField, stringField) FROM $table"),
-        sql(s"SELECT stringField FROM $table").map {
+        sql(s"SELECT stringField FROM $table").rdd.map {
           case Row(s: String) => Row(s + s)
         }.collect().toSeq)
     }