[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.

3 files changed, 4 insertions, 4 deletions

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) =>