[SPARK-17900][SQL] Graduate a list of Spark SQL APIs to stable

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

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 
 import scala.language.implicitConversions
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.internal.Logging
 import org.apache.spark.sql.catalyst.analysis._
 import org.apache.spark.sql.catalyst.encoders.{encoderFor, ExpressionEncoder}
@@ -1181,13 +1181,11 @@ class Column(protected[sql] val expr: Expression) extends Logging {
 
 
 /**
- * :: Experimental ::
  * A convenient class used for constructing schema.
  *
  * @since 1.3.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 class ColumnName(name: String) extends Column(name) {
 
   /**

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

@@ -21,20 +21,18 @@ import java.{lang => jl}
 
 import scala.collection.JavaConverters._
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types._
 
 
 /**
- * :: Experimental ::
  * Functionality for working with missing data in [[DataFrame]]s.
  *
  * @since 1.3.1
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 final class DataFrameNaFunctions private[sql](df: DataFrame) {
 
   /**

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

@@ -21,20 +21,18 @@ import java.{lang => jl, util => ju}
 
 import scala.collection.JavaConverters._
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.execution.stat._
 import org.apache.spark.sql.types._
 import org.apache.spark.util.sketch.{BloomFilter, CountMinSketch}
 
 /**
- * :: Experimental ::
  * Statistic functions for [[DataFrame]]s.
  *
  * @since 1.4.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 final class DataFrameStatFunctions private[sql](df: DataFrame) {
 
   /**

sql/core/src/main/scala/org/apache/spark/sql/expressions/UserDefinedFunction.scala

@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.expressions
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.catalyst.expressions.ScalaUDF
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.functions
@@ -39,13 +39,17 @@ import org.apache.spark.sql.types.DataType
  *
  * @since 1.3.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 case class UserDefinedFunction protected[sql] (
     f: AnyRef,
     dataType: DataType,
     inputTypes: Option[Seq[DataType]]) {
 
+  /**
+   * Returns an expression that invokes the UDF, using the given arguments.
+   *
+   * @since 1.3.0
+   */
   def apply(exprs: Column*): Column = {
     Column(ScalaUDF(f, dataType, exprs.map(_.expr), inputTypes.getOrElse(Nil)))
   }

sql/core/src/main/scala/org/apache/spark/sql/expressions/Window.scala

@@ -17,12 +17,11 @@
 
 package org.apache.spark.sql.expressions
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.catalyst.expressions._
 
 /**
- * :: Experimental ::
  * Utility functions for defining window in DataFrames.
  *
  * {{{
@@ -36,8 +35,7 @@ import org.apache.spark.sql.catalyst.expressions._
  *
  * @since 1.4.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 object Window {
 
   /**
@@ -164,7 +162,6 @@ object Window {
 }
 
 /**
- * :: Experimental ::
  * Utility functions for defining window in DataFrames.
  *
  * {{{
@@ -177,6 +174,5 @@ object Window {
  *
  * @since 1.4.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 class Window private()  // So we can see Window in JavaDoc.

sql/core/src/main/scala/org/apache/spark/sql/expressions/WindowSpec.scala

@@ -17,20 +17,18 @@
 
 package org.apache.spark.sql.expressions
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.catalyst.expressions._
 
 /**
- * :: Experimental ::
  * A window specification that defines the partitioning, ordering, and frame boundaries.
  *
  * Use the static methods in [[Window]] to create a [[WindowSpec]].
  *
  * @since 1.4.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 class WindowSpec private[sql](
     partitionSpec: Seq[Expression],
     orderSpec: Seq[SortOrder],

sql/core/src/main/scala/org/apache/spark/sql/expressions/udaf.scala

@@ -17,20 +17,18 @@
 
 package org.apache.spark.sql.expressions
 
-import org.apache.spark.annotation.{Experimental, InterfaceStability}
+import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.{Column, Row}
 import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
 import org.apache.spark.sql.execution.aggregate.ScalaUDAF
 import org.apache.spark.sql.types._
 
 /**
- * :: Experimental ::
  * The base class for implementing user-defined aggregate functions (UDAF).
  *
  * @since 1.5.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 abstract class UserDefinedAggregateFunction extends Serializable {
 
   /**
@@ -46,6 +44,8 @@ abstract class UserDefinedAggregateFunction extends Serializable {
    *
    * The name of a field of this [[StructType]] is only used to identify the corresponding
    * input argument. Users can choose names to identify the input arguments.
+   *
+   * @since 1.5.0
    */
   def inputSchema: StructType
 
@@ -63,17 +63,23 @@ abstract class UserDefinedAggregateFunction extends Serializable {
    *
    * The name of a field of this [[StructType]] is only used to identify the corresponding
    * buffer value. Users can choose names to identify the input arguments.
+   *
+   * @since 1.5.0
    */
   def bufferSchema: StructType
 
   /**
    * The [[DataType]] of the returned value of this [[UserDefinedAggregateFunction]].
+   *
+   * @since 1.5.0
    */
   def dataType: DataType
 
   /**
    * Returns true iff this function is deterministic, i.e. given the same input,
    * always return the same output.
+   *
+   * @since 1.5.0
    */
   def deterministic: Boolean
 
@@ -83,31 +89,41 @@ abstract class UserDefinedAggregateFunction extends Serializable {
    * The contract should be that applying the merge function on two initial buffers should just
    * return the initial buffer itself, i.e.
    * `merge(initialBuffer, initialBuffer)` should equal `initialBuffer`.
+   *
+   * @since 1.5.0
    */
   def initialize(buffer: MutableAggregationBuffer): Unit
 
   /**
    * Updates the given aggregation buffer `buffer` with new input data from `input`.
    *
    * This is called once per input row.
+   *
+   * @since 1.5.0
    */
   def update(buffer: MutableAggregationBuffer, input: Row): Unit
 
   /**
    * Merges two aggregation buffers and stores the updated buffer values back to `buffer1`.
    *
    * This is called when we merge two partially aggregated data together.
+   *
+   * @since 1.5.0
    */
   def merge(buffer1: MutableAggregationBuffer, buffer2: Row): Unit
 
   /**
    * Calculates the final result of this [[UserDefinedAggregateFunction]] based on the given
    * aggregation buffer.
+   *
+   * @since 1.5.0
    */
   def evaluate(buffer: Row): Any
 
   /**
    * Creates a [[Column]] for this UDAF using given [[Column]]s as input arguments.
+   *
+   * @since 1.5.0
    */
   @scala.annotation.varargs
   def apply(exprs: Column*): Column = {
@@ -122,6 +138,8 @@ abstract class UserDefinedAggregateFunction extends Serializable {
   /**
    * Creates a [[Column]] for this UDAF using the distinct values of the given
    * [[Column]]s as input arguments.
+   *
+   * @since 1.5.0
    */
   @scala.annotation.varargs
   def distinct(exprs: Column*): Column = {
@@ -135,15 +153,13 @@ abstract class UserDefinedAggregateFunction extends Serializable {
 }
 
 /**
- * :: Experimental ::
  * A [[Row]] representing a mutable aggregation buffer.
  *
  * This is not meant to be extended outside of Spark.
  *
  * @since 1.5.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 abstract class MutableAggregationBuffer extends Row {
 
   /** Update the ith value of this buffer. */

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

@@ -37,7 +37,6 @@ import org.apache.spark.util.Utils
 
 
 /**
- * :: Experimental ::
  * Functions available for DataFrame operations.
  *
  * @groupname udf_funcs UDF functions
@@ -53,8 +52,7 @@ import org.apache.spark.util.Utils
  * @groupname Ungrouped Support functions for DataFrames
  * @since 1.3.0
  */
-@Experimental
-@InterfaceStability.Evolving
+@InterfaceStability.Stable
 // scalastyle:off
 object functions {
 // scalastyle:on