[SPARK-15109][SQL] Accept Dataset[_] in joins

## What changes were proposed in this pull request?
This patch changes the join API in Dataset so they can accept any Dataset, rather than just DataFrames.

## How was this patch tested?
N/A.

Author: Reynold Xin <rxin@databricks.com>

Closes #12886 from rxin/SPARK-15109.

sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala

@@ -564,7 +564,7 @@ class Dataset[T] private[sql](
    * @group untypedrel
    * @since 2.0.0
    */
-  def join(right: DataFrame): DataFrame = withPlan {
+  def join(right: Dataset[_]): DataFrame = withPlan {
     Join(logicalPlan, right.logicalPlan, joinType = Inner, None)
   }
 
@@ -589,7 +589,7 @@ class Dataset[T] private[sql](
    * @group untypedrel
    * @since 2.0.0
    */
-  def join(right: DataFrame, usingColumn: String): DataFrame = {
+  def join(right: Dataset[_], usingColumn: String): DataFrame = {
     join(right, Seq(usingColumn))
   }
 
@@ -614,7 +614,7 @@ class Dataset[T] private[sql](
    * @group untypedrel
    * @since 2.0.0
    */
-  def join(right: DataFrame, usingColumns: Seq[String]): DataFrame = {
+  def join(right: Dataset[_], usingColumns: Seq[String]): DataFrame = {
     join(right, usingColumns, "inner")
   }
 
@@ -635,7 +635,7 @@ class Dataset[T] private[sql](
    * @group untypedrel
    * @since 2.0.0
    */
-  def join(right: DataFrame, usingColumns: Seq[String], joinType: String): DataFrame = {
+  def join(right: Dataset[_], usingColumns: Seq[String], joinType: String): DataFrame = {
     // Analyze the self join. The assumption is that the analyzer will disambiguate left vs right
     // by creating a new instance for one of the branch.
     val joined = sparkSession.executePlan(
@@ -663,7 +663,7 @@ class Dataset[T] private[sql](
    * @group untypedrel
    * @since 2.0.0
    */
-  def join(right: DataFrame, joinExprs: Column): DataFrame = join(right, joinExprs, "inner")
+  def join(right: Dataset[_], joinExprs: Column): DataFrame = join(right, joinExprs, "inner")
 
   /**
    * Join with another [[DataFrame]], using the given join expression. The following performs
@@ -686,7 +686,7 @@ class Dataset[T] private[sql](
    * @group untypedrel
    * @since 2.0.0
    */
-  def join(right: DataFrame, joinExprs: Column, joinType: String): DataFrame = {
+  def join(right: Dataset[_], joinExprs: Column, joinType: String): DataFrame = {
     // Note that in this function, we introduce a hack in the case of self-join to automatically
     // resolve ambiguous join conditions into ones that might make sense [SPARK-6231].
     // Consider this case: df.join(df, df("key") === df("key"))

sql/core/src/main/scala/org/apache/spark/sql/functions.scala

@@ -931,8 +931,8 @@ object functions {
    * @group normal_funcs
    * @since 1.5.0
    */
-  def broadcast(df: DataFrame): DataFrame = {
-    Dataset.ofRows(df.sparkSession, BroadcastHint(df.logicalPlan))
+  def broadcast[T](df: Dataset[T]): Dataset[T] = {
+    Dataset[T](df.sparkSession, BroadcastHint(df.logicalPlan))(df.unresolvedTEncoder)
   }
 
   /**