[SPARK-13817][BUILD][SQL] Re-enable MiMA and removes object DataFrame

## What changes were proposed in this pull request?

PR #11443 temporarily disabled MiMA check, this PR re-enables it.

One extra change is that `object DataFrame` is also removed. The only purpose of introducing `object DataFrame` was to use it as an internal factory for creating `Dataset[Row]`. By replacing this internal factory with `Dataset.newDataFrame`, both `DataFrame` and `DataFrame$` are entirely removed from the API, so that we can simply put a `MissingClassProblem` filter in `MimaExcludes.scala` for most DataFrame API  changes.

## How was this patch tested?

Tested by MiMA check triggered by Jenkins.

Author: Cheng Lian <lian@databricks.com>

Closes #11656 from liancheng/re-enable-mima.

15 files changed, 48 insertions, 50 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 17a91975f4..f1791e6943 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
@@ -48,18 +48,16 @@ import org.apache.spark.sql.types._
 import org.apache.spark.storage.StorageLevel
 import org.apache.spark.util.Utils
 
-private[sql] object DataFrame {
-  def apply(sqlContext: SQLContext, logicalPlan: LogicalPlan): DataFrame = {
-    val qe = sqlContext.executePlan(logicalPlan)
-    qe.assertAnalyzed()
-    new Dataset[Row](sqlContext, logicalPlan, RowEncoder(qe.analyzed.schema))
-  }
-}
-
 private[sql] object Dataset {
   def apply[T: Encoder](sqlContext: SQLContext, logicalPlan: LogicalPlan): Dataset[T] = {
     new Dataset(sqlContext, logicalPlan, implicitly[Encoder[T]])
   }
+
+  def newDataFrame(sqlContext: SQLContext, logicalPlan: LogicalPlan): DataFrame = {
+    val qe = sqlContext.executePlan(logicalPlan)
+    qe.assertAnalyzed()
+    new Dataset[Row](sqlContext, logicalPlan, RowEncoder(qe.analyzed.schema))
+  }
 }
 
 /**
@@ -2129,7 +2127,7 @@ class Dataset[T] private[sql](
 
   /** A convenient function to wrap a logical plan and produce a DataFrame. */
   @inline private def withPlan(logicalPlan: => LogicalPlan): DataFrame = {
-    DataFrame(sqlContext, logicalPlan)
+    Dataset.newDataFrame(sqlContext, logicalPlan)
   }
 
   /** A convenient function to wrap a logical plan and produce a DataFrame. */
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
index 822702429d..52b567ea25 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
@@ -128,7 +128,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
         userSpecifiedSchema = userSpecifiedSchema,
         className = source,
         options = extraOptions.toMap)
-    DataFrame(sqlContext, LogicalRelation(dataSource.resolveRelation()))
+    Dataset.newDataFrame(sqlContext, LogicalRelation(dataSource.resolveRelation()))
   }
 
   /**
@@ -175,7 +175,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
         userSpecifiedSchema = userSpecifiedSchema,
         className = source,
         options = extraOptions.toMap)
-    DataFrame(sqlContext, StreamingRelation(dataSource.createSource()))
+    Dataset.newDataFrame(sqlContext, StreamingRelation(dataSource.createSource()))
   }
 
   /**
@@ -345,7 +345,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
       InferSchema.infer(jsonRDD, sqlContext.conf.columnNameOfCorruptRecord, parsedOptions)
     }
 
-    DataFrame(
+    Dataset.newDataFrame(
       sqlContext,
       LogicalRDD(
         schema.toAttributes,
@@ -393,7 +393,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
    * @since 1.4.0
    */
   def table(tableName: String): DataFrame = {
-    DataFrame(sqlContext,
+    Dataset.newDataFrame(sqlContext,
       sqlContext.catalog.lookupRelation(sqlContext.sqlParser.parseTableIdentifier(tableName)))
   }
 
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 2a0f77349a..04d277bed2 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
@@ -55,17 +55,17 @@ class GroupedData protected[sql](
 
     groupType match {
       case GroupedData.GroupByType =>
-        DataFrame(
+        Dataset.newDataFrame(
           df.sqlContext, Aggregate(groupingExprs, aliasedAgg, df.logicalPlan))
       case GroupedData.RollupType =>
-        DataFrame(
+        Dataset.newDataFrame(
           df.sqlContext, Aggregate(Seq(Rollup(groupingExprs)), aliasedAgg, df.logicalPlan))
       case GroupedData.CubeType =>
-        DataFrame(
+        Dataset.newDataFrame(
           df.sqlContext, Aggregate(Seq(Cube(groupingExprs)), aliasedAgg, df.logicalPlan))
       case GroupedData.PivotType(pivotCol, values) =>
         val aliasedGrps = groupingExprs.map(alias)
-        DataFrame(
+        Dataset.newDataFrame(
           df.sqlContext, Pivot(aliasedGrps, pivotCol, values, aggExprs, df.logicalPlan))
     }
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala b/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
index 1639cc8db6..472ae716f1 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
@@ -64,7 +64,7 @@ class GroupedDataset[K, V] private[sql](
 
   private def groupedData =
     new GroupedData(
-      DataFrame(sqlContext, logicalPlan), groupingAttributes, GroupedData.GroupByType)
+      Dataset.newDataFrame(sqlContext, logicalPlan), groupingAttributes, GroupedData.GroupByType)
 
   /**
    * Returns a new [[GroupedDataset]] where the type of the key has been mapped to the specified
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 54dbd6bda5..49a70a7c5f 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
@@ -374,7 +374,7 @@ class SQLContext private[sql](
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
     val attributeSeq = schema.toAttributes
     val rowRDD = RDDConversions.productToRowRdd(rdd, schema.map(_.dataType))
-    DataFrame(self, LogicalRDD(attributeSeq, rowRDD)(self))
+    Dataset.newDataFrame(self, LogicalRDD(attributeSeq, rowRDD)(self))
   }
 
   /**
@@ -389,7 +389,7 @@ class SQLContext private[sql](
     SQLContext.setActive(self)
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
     val attributeSeq = schema.toAttributes
-    DataFrame(self, LocalRelation.fromProduct(attributeSeq, data))
+    Dataset.newDataFrame(self, LocalRelation.fromProduct(attributeSeq, data))
   }
 
   /**
@@ -399,7 +399,7 @@ class SQLContext private[sql](
    * @since 1.3.0
    */
   def baseRelationToDataFrame(baseRelation: BaseRelation): DataFrame = {
-    DataFrame(this, LogicalRelation(baseRelation))
+    Dataset.newDataFrame(this, LogicalRelation(baseRelation))
   }
 
   /**
@@ -454,7 +454,7 @@ class SQLContext private[sql](
       rowRDD.map{r: Row => InternalRow.fromSeq(r.toSeq)}
     }
     val logicalPlan = LogicalRDD(schema.toAttributes, catalystRows)(self)
-    DataFrame(this, logicalPlan)
+    Dataset.newDataFrame(this, logicalPlan)
   }
 
 
@@ -489,7 +489,7 @@ class SQLContext private[sql](
     // TODO: use MutableProjection when rowRDD is another DataFrame and the applied
     // schema differs from the existing schema on any field data type.
     val logicalPlan = LogicalRDD(schema.toAttributes, catalystRows)(self)
-    DataFrame(this, logicalPlan)
+    Dataset.newDataFrame(this, logicalPlan)
   }
 
   /**
@@ -517,7 +517,7 @@ class SQLContext private[sql](
    */
   @DeveloperApi
   def createDataFrame(rows: java.util.List[Row], schema: StructType): DataFrame = {
-    DataFrame(self, LocalRelation.fromExternalRows(schema.toAttributes, rows.asScala))
+    Dataset.newDataFrame(self, LocalRelation.fromExternalRows(schema.toAttributes, rows.asScala))
   }
 
   /**
@@ -536,7 +536,7 @@ class SQLContext private[sql](
       val localBeanInfo = Introspector.getBeanInfo(Utils.classForName(className))
       SQLContext.beansToRows(iter, localBeanInfo, attributeSeq)
     }
-    DataFrame(this, LogicalRDD(attributeSeq, rowRdd)(this))
+    Dataset.newDataFrame(this, LogicalRDD(attributeSeq, rowRdd)(this))
   }
 
   /**
@@ -564,7 +564,7 @@ class SQLContext private[sql](
     val className = beanClass.getName
     val beanInfo = Introspector.getBeanInfo(beanClass)
     val rows = SQLContext.beansToRows(data.asScala.iterator, beanInfo, attrSeq)
-    DataFrame(self, LocalRelation(attrSeq, rows.toSeq))
+    Dataset.newDataFrame(self, LocalRelation(attrSeq, rows.toSeq))
   }
 
   /**
@@ -770,7 +770,7 @@ class SQLContext private[sql](
    */
   @Experimental
   def range(start: Long, end: Long, step: Long, numPartitions: Int): DataFrame = {
-    DataFrame(this, Range(start, end, step, numPartitions))
+    Dataset.newDataFrame(this, Range(start, end, step, numPartitions))
   }
 
   /**
@@ -781,7 +781,7 @@ class SQLContext private[sql](
    * @since 1.3.0
    */
   def sql(sqlText: String): DataFrame = {
-    DataFrame(this, parseSql(sqlText))
+    Dataset.newDataFrame(this, parseSql(sqlText))
   }
 
   /**
@@ -795,7 +795,7 @@ class SQLContext private[sql](
   }
 
   private def table(tableIdent: TableIdentifier): DataFrame = {
-    DataFrame(this, catalog.lookupRelation(tableIdent))
+    Dataset.newDataFrame(this, catalog.lookupRelation(tableIdent))
   }
 
   /**
@@ -807,7 +807,7 @@ class SQLContext private[sql](
    * @since 1.3.0
    */
   def tables(): DataFrame = {
-    DataFrame(this, ShowTablesCommand(None))
+    Dataset.newDataFrame(this, ShowTablesCommand(None))
   }
 
   /**
@@ -819,7 +819,7 @@ class SQLContext private[sql](
    * @since 1.3.0
    */
   def tables(databaseName: String): DataFrame = {
-    DataFrame(this, ShowTablesCommand(Some(databaseName)))
+    Dataset.newDataFrame(this, ShowTablesCommand(Some(databaseName)))
   }
 
   /**
@@ -886,7 +886,7 @@ class SQLContext private[sql](
       schema: StructType): DataFrame = {
 
     val rowRdd = rdd.map(r => python.EvaluatePython.fromJava(r, schema).asInstanceOf[InternalRow])
-    DataFrame(this, LogicalRDD(schema.toAttributes, rowRdd)(self))
+    Dataset.newDataFrame(this, LogicalRDD(schema.toAttributes, rowRdd)(self))
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/command/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/command/commands.scala
index 877456ca48..54cdcb10ac 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/command/commands.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/command/commands.scala
@@ -21,7 +21,7 @@ import java.util.NoSuchElementException
 
 import org.apache.spark.Logging
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.{DataFrame, Row, SQLContext}
+import org.apache.spark.sql.{Dataset, Row, SQLContext}
 import org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow}
 import org.apache.spark.sql.catalyst.errors.TreeNodeException
 import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference}
@@ -252,7 +252,7 @@ case class CacheTableCommand(
 
   override def run(sqlContext: SQLContext): Seq[Row] = {
     plan.foreach { logicalPlan =>
-      sqlContext.registerDataFrameAsTable(DataFrame(sqlContext, logicalPlan), tableName)
+      sqlContext.registerDataFrameAsTable(Dataset.newDataFrame(sqlContext, logicalPlan), tableName)
     }
     sqlContext.cacheTable(tableName)
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
index 60ec67c8f0..887f5469b5 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
@@ -27,7 +27,7 @@ import org.apache.hadoop.fs.Path
 
 import org.apache.spark.Logging
 import org.apache.spark.deploy.SparkHadoopUtil
-import org.apache.spark.sql.{AnalysisException, DataFrame, SaveMode, SQLContext}
+import org.apache.spark.sql._
 import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
 import org.apache.spark.sql.execution.streaming.{FileStreamSource, Sink, Source}
 import org.apache.spark.sql.sources._
@@ -154,7 +154,7 @@ case class DataSource(
         }
 
         def dataFrameBuilder(files: Array[String]): DataFrame = {
-          DataFrame(
+          Dataset.newDataFrame(
             sqlContext,
             LogicalRelation(
               DataSource(
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoDataSource.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoDataSource.scala
index abb1628590..9cf794804d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoDataSource.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoDataSource.scala
@@ -34,7 +34,7 @@ private[sql] case class InsertIntoDataSource(
 
   override def run(sqlContext: SQLContext): Seq[Row] = {
     val relation = logicalRelation.relation.asInstanceOf[InsertableRelation]
-    val data = DataFrame(sqlContext, query)
+    val data = Dataset.newDataFrame(sqlContext, query)
     // Apply the schema of the existing table to the new data.
     val df = sqlContext.internalCreateDataFrame(data.queryExecution.toRdd, logicalRelation.schema)
     relation.insert(df, overwrite)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoHadoopFsRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoHadoopFsRelation.scala
index fb52730104..51ec969daf 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoHadoopFsRelation.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoHadoopFsRelation.scala
@@ -114,7 +114,7 @@ private[sql] case class InsertIntoHadoopFsRelation(
       val partitionSet = AttributeSet(partitionColumns)
       val dataColumns = query.output.filterNot(partitionSet.contains)
 
-      val queryExecution = DataFrame(sqlContext, query).queryExecution
+      val queryExecution = Dataset.newDataFrame(sqlContext, query).queryExecution
       SQLExecution.withNewExecutionId(sqlContext, queryExecution) {
         val relation =
           WriteRelation(
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ddl.scala
index 895794c4c2..903c9913ac 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ddl.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ddl.scala
@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.execution.datasources
 
-import org.apache.spark.sql.{DataFrame, Row, SaveMode, SQLContext}
+import org.apache.spark.sql._
 import org.apache.spark.sql.catalyst.TableIdentifier
 import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference}
 import org.apache.spark.sql.catalyst.plans.logical
@@ -100,7 +100,7 @@ case class CreateTempTableUsing(
       options = options)
     sqlContext.catalog.registerTable(
       tableIdent,
-      DataFrame(sqlContext, LogicalRelation(dataSource.resolveRelation())).logicalPlan)
+      Dataset.newDataFrame(sqlContext, LogicalRelation(dataSource.resolveRelation())).logicalPlan)
 
     Seq.empty[Row]
   }
@@ -115,7 +115,7 @@ case class CreateTempTableUsingAsSelect(
     query: LogicalPlan) extends RunnableCommand {
 
   override def run(sqlContext: SQLContext): Seq[Row] = {
-    val df = DataFrame(sqlContext, query)
+    val df = Dataset.newDataFrame(sqlContext, query)
     val dataSource = DataSource(
       sqlContext,
       className = provider,
@@ -125,7 +125,7 @@ case class CreateTempTableUsingAsSelect(
     val result = dataSource.write(mode, df)
     sqlContext.catalog.registerTable(
       tableIdent,
-      DataFrame(sqlContext, LogicalRelation(result)).logicalPlan)
+      Dataset.newDataFrame(sqlContext, LogicalRelation(result)).logicalPlan)
 
     Seq.empty[Row]
   }
@@ -146,7 +146,7 @@ case class RefreshTable(tableIdent: TableIdentifier)
     if (isCached) {
       // Create a data frame to represent the table.
       // TODO: Use uncacheTable once it supports database name.
-      val df = DataFrame(sqlContext, logicalPlan)
+      val df = Dataset.newDataFrame(sqlContext, logicalPlan)
       // Uncache the logicalPlan.
       sqlContext.cacheManager.tryUncacheQuery(df, blocking = true)
       // Cache it again.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
index 0dc34814fb..b912c5cc1d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
@@ -20,7 +20,7 @@ package org.apache.spark.sql.execution.stat
 import scala.collection.mutable.{Map => MutableMap}
 
 import org.apache.spark.Logging
-import org.apache.spark.sql.{Column, DataFrame, Row}
+import org.apache.spark.sql.{Column, DataFrame, Dataset, Row}
 import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
 import org.apache.spark.sql.types._
 
@@ -121,6 +121,6 @@ private[sql] object FrequentItems extends Logging {
       StructField(v._1 + "_freqItems", ArrayType(v._2, false))
     }
     val schema = StructType(outputCols).toAttributes
-    DataFrame(df.sqlContext, LocalRelation.fromExternalRows(schema, Seq(resultRow)))
+    Dataset.newDataFrame(df.sqlContext, LocalRelation.fromExternalRows(schema, Seq(resultRow)))
   }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
index daa065e5cd..71fd185b16 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
@@ -20,7 +20,7 @@ package org.apache.spark.sql.execution.stat
 import scala.collection.mutable.ArrayBuffer
 
 import org.apache.spark.Logging
-import org.apache.spark.sql.{Column, DataFrame, Row}
+import org.apache.spark.sql.{Column, DataFrame, Dataset, Row}
 import org.apache.spark.sql.catalyst.expressions.{Cast, GenericMutableRow}
 import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
 import org.apache.spark.sql.functions._
@@ -454,6 +454,6 @@ private[sql] object StatFunctions extends Logging {
     }
     val schema = StructType(StructField(tableName, StringType) +: headerNames)
 
-    DataFrame(df.sqlContext, LocalRelation(schema.toAttributes, table)).na.fill(0.0)
+    Dataset.newDataFrame(df.sqlContext, LocalRelation(schema.toAttributes, table)).na.fill(0.0)
   }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
index 7d7c51b158..4a0eb46b22 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
@@ -211,7 +211,7 @@ class StreamExecution(
 
         // Construct the batch and send it to the sink.
         val batchOffset = streamProgress.toCompositeOffset(sources)
-        val nextBatch = new Batch(batchOffset, DataFrame(sqlContext, newPlan))
+        val nextBatch = new Batch(batchOffset, Dataset.newDataFrame(sqlContext, newPlan))
         sink.addBatch(nextBatch)
       }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/memory.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/memory.scala
index 3b764c5558..096477ce0e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/memory.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/memory.scala
@@ -59,7 +59,7 @@ case class MemoryStream[A : Encoder](id: Int, sqlContext: SQLContext)
   }
 
   def toDF()(implicit sqlContext: SQLContext): DataFrame = {
-    DataFrame(sqlContext, logicalPlan)
+    Dataset.newDataFrame(sqlContext, logicalPlan)
   }
 
   def addData(data: A*): Offset = {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
index 86412c3489..737e125f6c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
@@ -936,7 +936,7 @@ object functions extends LegacyFunctions {
    * @since 1.5.0
    */
   def broadcast(df: DataFrame): DataFrame = {
-    DataFrame(df.sqlContext, BroadcastHint(df.logicalPlan))
+    Dataset.newDataFrame(df.sqlContext, BroadcastHint(df.logicalPlan))
   }
 
   /**