[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.

33 files changed, 78 insertions, 69 deletions

diff --git a/dev/run-tests.py b/dev/run-tests.py
index ebeede52c9..a1e6f1bdb5 100755
--- a/dev/run-tests.py
+++ b/dev/run-tests.py
@@ -573,8 +573,7 @@ def main():
     # backwards compatibility checks
     if build_tool == "sbt":
         # Note: compatibility tests only supported in sbt for now
-        # TODO Temporarily disable MiMA check for DF-to-DS migration prototyping
-        # detect_binary_inop_with_mima()
+        detect_binary_inop_with_mima()
         # Since we did not build assembly/assembly before running dev/mima, we need to
         # do it here because the tests still rely on it; see SPARK-13294 for details.
         build_spark_assembly_sbt(hadoop_version)
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaAFTSurvivalRegressionExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaAFTSurvivalRegressionExample.java
index 39053109da..22b93a3a85 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaAFTSurvivalRegressionExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaAFTSurvivalRegressionExample.java
@@ -26,7 +26,6 @@ import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.ml.regression.AFTSurvivalRegression;
 import org.apache.spark.ml.regression.AFTSurvivalRegressionModel;
 import org.apache.spark.mllib.linalg.*;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
index 9754ba5268..088037d427 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
@@ -31,7 +31,6 @@ import org.apache.spark.api.java.function.Function;
 import org.apache.spark.ml.evaluation.RegressionEvaluator;
 import org.apache.spark.ml.recommendation.ALS;
 import org.apache.spark.ml.recommendation.ALSModel;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.types.DataTypes;
 // $example off$
 
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java
index 84eef1fb8a..d554377975 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java
@@ -27,7 +27,6 @@ import java.util.Arrays;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.ml.feature.Binarizer;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
 import org.apache.spark.sql.types.DataTypes;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
index fb6c47be39..90bc94c45b 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
@@ -33,7 +33,6 @@ import org.apache.spark.ml.param.ParamMap;
 import org.apache.spark.ml.tuning.CrossValidator;
 import org.apache.spark.ml.tuning.CrossValidatorModel;
 import org.apache.spark.ml.tuning.ParamGridBuilder;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SQLContext;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
index e568bea607..e8ae100d68 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
@@ -33,7 +33,6 @@ import org.apache.spark.mllib.linalg.BLAS;
 import org.apache.spark.mllib.linalg.Vector;
 import org.apache.spark.mllib.linalg.Vectors;
 import org.apache.spark.mllib.regression.LabeledPoint;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SQLContext;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java
index 8a02f60aa4..f13698ae5e 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java
@@ -29,7 +29,6 @@ import org.apache.spark.ml.classification.LogisticRegressionModel;
 import org.apache.spark.ml.param.ParamMap;
 import org.apache.spark.mllib.linalg.Vectors;
 import org.apache.spark.mllib.regression.LabeledPoint;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 // $example off$
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaKMeansExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaKMeansExample.java
index 30ccf30885..c5022f4c0b 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaKMeansExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaKMeansExample.java
@@ -32,7 +32,6 @@ import org.apache.spark.ml.clustering.KMeans;
 import org.apache.spark.mllib.linalg.Vector;
 import org.apache.spark.mllib.linalg.VectorUDT;
 import org.apache.spark.mllib.linalg.Vectors;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.types.Metadata;
 import org.apache.spark.sql.types.StructField;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaLDAExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaLDAExample.java
index c70d44c297..351bc40118 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaLDAExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaLDAExample.java
@@ -28,7 +28,6 @@ import org.apache.spark.ml.clustering.LDAModel;
 import org.apache.spark.mllib.linalg.Vector;
 import org.apache.spark.mllib.linalg.VectorUDT;
 import org.apache.spark.mllib.linalg.Vectors;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SQLContext;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaOneVsRestExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaOneVsRestExample.java
index 8288f73c1b..1f13b48bf8 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaOneVsRestExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaOneVsRestExample.java
@@ -29,7 +29,6 @@ import org.apache.spark.ml.util.MetadataUtils;
 import org.apache.spark.mllib.evaluation.MulticlassMetrics;
 import org.apache.spark.mllib.linalg.Matrix;
 import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SQLContext;
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaSQLTransformerExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaSQLTransformerExample.java
index e413cbaf71..7e3ca99d7c 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaSQLTransformerExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaSQLTransformerExample.java
@@ -24,7 +24,6 @@ import org.apache.spark.SparkConf;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.ml.feature.SQLTransformer;
-import org.apache.spark.sql.DataFrame;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala
index 45776fbb9f..567a717b9d 100644
--- a/project/MimaExcludes.scala
+++ b/project/MimaExcludes.scala
@@ -296,6 +296,28 @@ object MimaExcludes {
         // SPARK-12073: backpressure rate controller consumes events preferentially from lagging partitions
         ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.kafka.KafkaTestUtils.createTopic"),
         ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.kafka.DirectKafkaInputDStream.maxMessagesPerPartition")
+      ) ++ Seq(
+        // [SPARK-13244][SQL] Migrates DataFrame to Dataset
+        ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.sql.DataFrameHolder.apply"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.DataFrameHolder.toDF"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.DataFrameHolder.toDF"),
+        ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.sql.DataFrameHolder.copy"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.DataFrameHolder.copy$default$1"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.DataFrameHolder.df$1"),
+        ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.sql.DataFrameHolder.this"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.tables"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.tables"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.sql"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.baseRelationToDataFrame"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.table"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.DataFrame.apply"),
+
+        ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.DataFrame"),
+        ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.DataFrame$"),
+
+        ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.mllib.evaluation.MultilabelMetrics.this"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.classification.LogisticRegressionSummary.predictions"),
+        ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.ml.classification.LogisticRegressionSummary.predictions")
       )
     case v if v.startsWith("1.6") =>
       Seq(
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))
   }
 
   /**
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index f4a5107eaf..46cd380a79 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -933,7 +933,7 @@ class DataFrameSuite extends QueryTest with SharedSQLContext {
       assert(e2.getMessage.contains("Inserting into an RDD-based table is not allowed."))
 
       // error case: insert into an OneRowRelation
-      DataFrame(sqlContext, OneRowRelation).registerTempTable("one_row")
+      Dataset.newDataFrame(sqlContext, OneRowRelation).registerTempTable("one_row")
       val e3 = intercept[AnalysisException] {
         insertion.write.insertInto("one_row")
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala b/sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala
index 493a5a6437..7a5b639115 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala
@@ -65,7 +65,7 @@ import org.apache.spark.sql.execution.streaming._
 trait StreamTest extends QueryTest with Timeouts {
 
   implicit class RichSource(s: Source) {
-    def toDF(): DataFrame = DataFrame(sqlContext, StreamingRelation(s))
+    def toDF(): DataFrame = Dataset.newDataFrame(sqlContext, StreamingRelation(s))
 
     def toDS[A: Encoder](): Dataset[A] = Dataset(sqlContext, StreamingRelation(s))
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/test/SQLTestUtils.scala b/sql/core/src/test/scala/org/apache/spark/sql/test/SQLTestUtils.scala
index a7592e5d8d..2bce74571d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/test/SQLTestUtils.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/test/SQLTestUtils.scala
@@ -219,7 +219,7 @@ private[sql] trait SQLTestUtils
    * way to construct [[DataFrame]] directly out of local data without relying on implicits.
    */
   protected implicit def logicalPlanToSparkQuery(plan: LogicalPlan): DataFrame = {
-    DataFrame(sqlContext, plan)
+    Dataset.newDataFrame(sqlContext, plan)
   }
 
   /**
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala
index 7e4fb8b0ac..c4723fcb82 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala
@@ -246,7 +246,7 @@ case class CreateMetastoreDataSourceAsSelect(
       createMetastoreTable = true
     }
 
-    val data = DataFrame(hiveContext, query)
+    val data = Dataset.newDataFrame(hiveContext, query)
     val df = existingSchema match {
       // If we are inserting into an existing table, just use the existing schema.
       case Some(s) => sqlContext.internalCreateDataFrame(data.queryExecution.toRdd, s)
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/SQLBuilderTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/SQLBuilderTest.scala
index a0a0d134da..047e82e411 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/SQLBuilderTest.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/SQLBuilderTest.scala
@@ -19,7 +19,7 @@ package org.apache.spark.sql.hive
 
 import scala.util.control.NonFatal
 
-import org.apache.spark.sql.{DataFrame, QueryTest}
+import org.apache.spark.sql.{DataFrame, Dataset, QueryTest}
 import org.apache.spark.sql.catalyst.expressions.Expression
 import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
 import org.apache.spark.sql.hive.test.TestHiveSingleton
@@ -63,7 +63,7 @@ abstract class SQLBuilderTest extends QueryTest with TestHiveSingleton {
            """.stripMargin)
     }
 
-    checkAnswer(sqlContext.sql(generatedSQL), DataFrame(sqlContext, plan))
+    checkAnswer(sqlContext.sql(generatedSQL), Dataset.newDataFrame(sqlContext, plan))
   }
 
   protected def checkSQL(df: DataFrame, expectedSQL: String): Unit = {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
index d5a4295d62..5c26aa1a79 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
@@ -968,7 +968,7 @@ class TungstenAggregationQueryWithControlledFallbackSuite extends AggregationQue
         // Create a new df to make sure its physical operator picks up
         // spark.sql.TungstenAggregate.testFallbackStartsAt.
         // todo: remove it?
-        val newActual = DataFrame(sqlContext, actual.logicalPlan)
+        val newActual = Dataset.newDataFrame(sqlContext, actual.logicalPlan)
 
         QueryTest.checkAnswer(newActual, expectedAnswer) match {
           case Some(errorMessage) =>