1 files changed, 0 insertions, 28 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamReader.scala b/sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamReader.scala
index d437c16a25..864a9cd3eb 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamReader.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamReader.scala
@@ -35,89 +35,73 @@ import org.apache.spark.sql.types.StructType
 @Experimental
 final class DataStreamReader private[sql](sparkSession: SparkSession) extends Logging {
   /**
-   * :: Experimental ::
    * Specifies the input data source format.
    *
    * @since 2.0.0
    */
-  @Experimental
   def format(source: String): DataStreamReader = {
     this.source = source
     this
   }
 
   /**
-   * :: Experimental ::
    * Specifies the input schema. Some data sources (e.g. JSON) can infer the input schema
    * automatically from data. By specifying the schema here, the underlying data source can
    * skip the schema inference step, and thus speed up data loading.
    *
    * @since 2.0.0
    */
-  @Experimental
   def schema(schema: StructType): DataStreamReader = {
     this.userSpecifiedSchema = Option(schema)
     this
   }
 
   /**
-   * :: Experimental ::
    * Adds an input option for the underlying data source.
    *
    * @since 2.0.0
    */
-  @Experimental
   def option(key: String, value: String): DataStreamReader = {
     this.extraOptions += (key -> value)
     this
   }
 
   /**
-   * :: Experimental ::
    * Adds an input option for the underlying data source.
    *
    * @since 2.0.0
    */
-  @Experimental
   def option(key: String, value: Boolean): DataStreamReader = option(key, value.toString)
 
   /**
-   * :: Experimental ::
    * Adds an input option for the underlying data source.
    *
    * @since 2.0.0
    */
-  @Experimental
   def option(key: String, value: Long): DataStreamReader = option(key, value.toString)
 
   /**
-   * :: Experimental ::
    * Adds an input option for the underlying data source.
    *
    * @since 2.0.0
    */
-  @Experimental
   def option(key: String, value: Double): DataStreamReader = option(key, value.toString)
 
   /**
-   * :: Experimental ::
    * (Scala-specific) Adds input options for the underlying data source.
    *
    * @since 2.0.0
    */
-  @Experimental
   def options(options: scala.collection.Map[String, String]): DataStreamReader = {
     this.extraOptions ++= options
     this
   }
 
   /**
-   * :: Experimental ::
    * Adds input options for the underlying data source.
    *
    * @since 2.0.0
    */
-  @Experimental
   def options(options: java.util.Map[String, String]): DataStreamReader = {
     this.options(options.asScala)
     this
@@ -125,13 +109,11 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
 
 
   /**
-   * :: 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 load(): DataFrame = {
     val dataSource =
       DataSource(
@@ -143,18 +125,15 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
   }
 
   /**
-   * :: Experimental ::
    * Loads input in as a [[DataFrame]], for data streams that read from some path.
    *
    * @since 2.0.0
    */
-  @Experimental
   def load(path: String): DataFrame = {
     option("path", path).load()
   }
 
   /**
-   * :: Experimental ::
    * Loads a JSON file stream (one object per line) and returns the result as a [[DataFrame]].
    *
    * This function goes through the input once to determine the input schema. If you know the
@@ -198,11 +177,9 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
    *
    * @since 2.0.0
    */
-  @Experimental
   def json(path: String): DataFrame = format("json").load(path)
 
   /**
-   * :: Experimental ::
    * Loads a CSV file stream and returns the result as a [[DataFrame]].
    *
    * This function will go through the input once to determine the input schema if `inferSchema`
@@ -262,11 +239,9 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
    *
    * @since 2.0.0
    */
-  @Experimental
   def csv(path: String): DataFrame = format("csv").load(path)
 
   /**
-   * :: Experimental ::
    * Loads a Parquet file stream, returning the result as a [[DataFrame]].
    *
    * You can set the following Parquet-specific option(s) for reading Parquet files:
@@ -281,13 +256,11 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
    *
    * @since 2.0.0
    */
-  @Experimental
   def parquet(path: String): DataFrame = {
     format("parquet").load(path)
   }
 
   /**
-   * :: Experimental ::
    * Loads text files and returns a [[DataFrame]] whose schema starts with a string column named
    * "value", and followed by partitioned columns if there are any.
    *
@@ -308,7 +281,6 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
    *
    * @since 2.0.0
    */
-  @Experimental
   def text(path: String): DataFrame = format("text").load(path)