From 99dfcedbfd4c83c7b6a343456f03e8c6e29968c5 Mon Sep 17 00:00:00 2001 From: Cheng Lian Date: Sat, 27 Feb 2016 00:28:30 +0800 Subject: [SPARK-13457][SQL] Removes DataFrame RDD operations ## What changes were proposed in this pull request? This is another try of PR #11323. This PR removes DataFrame RDD operations except for `foreach` and `foreachPartitions` (they are actions rather than transformations). Original calls are now replaced by calls to methods of `DataFrame.rdd`. PR #11323 was reverted because it introduced a regression: both `DataFrame.foreach` and `DataFrame.foreachPartitions` wrap underlying RDD operations with `withNewExecutionId` to track Spark jobs. But they are removed in #11323. ## How was the this patch tested? No extra tests are added. Existing tests should do the work. Author: Cheng Lian Closes #11388 from liancheng/remove-df-rdd-ops. --- .../scala/org/apache/spark/sql/DataFrame.scala | 24 ---------------------- .../scala/org/apache/spark/sql/GroupedData.scala | 1 + .../org/apache/spark/sql/api/r/SQLUtils.scala | 2 +- .../apache/spark/sql/DataFrameAggregateSuite.scala | 2 +- .../datasources/parquet/ParquetFilterSuite.scala | 2 +- .../datasources/parquet/ParquetIOSuite.scala | 2 +- 6 files changed, 5 insertions(+), 28 deletions(-) (limited to 'sql/core/src') 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..5f5b7f4c19 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 @@ -1426,30 +1426,6 @@ 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 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/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") } -- cgit v1.2.3