[SPARK-15261][SQL] Remove experimental tag from DataFrameReader/Writer

## What changes were proposed in this pull request?
This patch removes experimental tag from DataFrameReader and DataFrameWriter, and explicitly tags a few methods added for structured streaming as experimental.

## How was this patch tested?
N/A

Author: Reynold Xin <rxin@databricks.com>

Closes #13038 from rxin/SPARK-15261.

2 files changed, 14 insertions, 8 deletions

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 5bf696c1c3..15d09e3edd 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
@@ -34,13 +34,11 @@ import org.apache.spark.sql.execution.streaming.StreamingRelation
 import org.apache.spark.sql.types.StructType
 
 /**
- * :: Experimental ::
- * Interface used to load a [[DataFrame]] from external storage systems (e.g. file systems,
+ * Interface used to load a [[Dataset]] from external storage systems (e.g. file systems,
  * key-value stores, etc) or data streams. Use [[SparkSession.read]] to access this.
  *
  * @since 1.4.0
  */
-@Experimental
 class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
 
   /**
@@ -164,11 +162,13 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
   }
 
   /**
+   * :: Experimental ::
    * Loads input data stream in as a [[DataFrame]], for data streams that don't require a path
    * (e.g. external key-value stores).
    *
    * @since 2.0.0
    */
+  @Experimental
   def stream(): DataFrame = {
     val dataSource =
       DataSource(
@@ -180,10 +180,12 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
   }
 
   /**
+   * :: Experimental ::
    * Loads input in as a [[DataFrame]], for data streams that read from some path.
    *
    * @since 2.0.0
    */
+  @Experimental
   def stream(path: String): DataFrame = {
     option("path", path).stream()
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala
index 6b1ccbec61..da9d25443e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala
@@ -34,13 +34,11 @@ import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.util.Utils
 
 /**
- * :: Experimental ::
- * Interface used to write a [[DataFrame]] to external storage systems (e.g. file systems,
- * key-value stores, etc) or data streams. Use [[DataFrame.write]] to access this.
+ * Interface used to write a [[Dataset]] to external storage systems (e.g. file systems,
+ * key-value stores, etc) or data streams. Use [[Dataset.write]] to access this.
  *
  * @since 1.4.0
  */
-@Experimental
 final class DataFrameWriter private[sql](df: DataFrame) {
 
   /**
@@ -255,11 +253,13 @@ final class DataFrameWriter private[sql](df: DataFrame) {
   }
 
   /**
+   * :: Experimental ::
    * Specifies the name of the [[ContinuousQuery]] that can be started with `startStream()`.
    * This name must be unique among all the currently active queries in the associated SQLContext.
    *
    * @since 2.0.0
    */
+  @Experimental
   def queryName(queryName: String): DataFrameWriter = {
     assertStreaming("queryName() can only be called on continuous queries")
     this.extraOptions += ("queryName" -> queryName)
@@ -267,25 +267,29 @@ final class DataFrameWriter private[sql](df: DataFrame) {
   }
 
   /**
+   * :: Experimental ::
    * Starts the execution of the streaming query, which will continually output results to the given
    * path as new data arrives. The returned [[ContinuousQuery]] object can be used to interact with
    * the stream.
    *
    * @since 2.0.0
    */
+  @Experimental
   def startStream(path: String): ContinuousQuery = {
     option("path", path).startStream()
   }
 
   /**
+   * :: Experimental ::
    * Starts the execution of the streaming query, which will continually output results to the given
    * path as new data arrives. The returned [[ContinuousQuery]] object can be used to interact with
    * the stream.
    *
    * @since 2.0.0
    */
+  @Experimental
   def startStream(): ContinuousQuery = {
-    assertNotBucketed
+    assertNotBucketed()
     assertStreaming("startStream() can only be called on continuous queries")
 
     if (source == "memory") {