[2/2] spark git commit: [SPARK-7588] Document all SQL/DataFrame public methods with @since tag

[rxin]

[SPARK-7588] Document all SQL/DataFrame public methods with @since tag

This pull request adds since tag to all public methods/classes in SQL/DataFrame 
to indicate which version the methods/classes were first added.

Author: Reynold Xin <r...@databricks.com>

Closes #6101 from rxin/tbc and squashes the following commits:

ed55e11 [Reynold Xin] Add since version to all DataFrame methods.

(cherry picked from commit 8fd55358b7fc1c7545d823bef7b39769f731c1ee)
Signed-off-by: Reynold Xin <r...@databricks.com>


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/bdd5db9f
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/bdd5db9f
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/bdd5db9f

Branch: refs/heads/branch-1.4
Commit: bdd5db9f16bc5fc18357b504781cf76774f9acd6
Parents: 2cc3301
Author: Reynold Xin <r...@databricks.com>
Authored: Tue May 12 18:37:02 2015 -0700
Committer: Reynold Xin <r...@databricks.com>
Committed: Tue May 12 18:37:10 2015 -0700

----------------------------------------------------------------------
 .../java/org/apache/spark/sql/SaveMode.java     |  10 ++
 .../scala/org/apache/spark/sql/Column.scala     | 145 +++++++++++++++++--
 .../scala/org/apache/spark/sql/DataFrame.scala  | 103 +++++++++++++
 .../org/apache/spark/sql/DataFrameHolder.scala  |   2 +
 .../apache/spark/sql/DataFrameNaFunctions.scala |  44 ++++++
 .../spark/sql/DataFrameStatFunctions.scala      |  18 +++
 .../apache/spark/sql/ExperimentalMethods.scala  |   4 +
 .../org/apache/spark/sql/GroupedData.scala      |  22 +++
 .../apache/spark/sql/JavaTypeInference.scala    |   3 +-
 .../scala/org/apache/spark/sql/SQLContext.scala |  94 +++++++++++-
 .../org/apache/spark/sql/SparkSQLParser.scala   |   1 -
 .../org/apache/spark/sql/UDFRegistration.scala  |  49 +++++++
 .../apache/spark/sql/UserDefinedFunction.scala  |   4 +
 .../scala/org/apache/spark/sql/functions.scala  | 140 +++++++++++++++++-
 .../org/apache/spark/sql/sources/filters.scala  |  30 ++++
 .../apache/spark/sql/sources/interfaces.scala   |  57 ++++++++
 .../org/apache/spark/sql/hive/HiveContext.scala |   6 +
 17 files changed, 706 insertions(+), 26 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/java/org/apache/spark/sql/SaveMode.java
----------------------------------------------------------------------
diff --git a/sql/core/src/main/java/org/apache/spark/sql/SaveMode.java 
b/sql/core/src/main/java/org/apache/spark/sql/SaveMode.java
index a40be52..9665c3c 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/SaveMode.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/SaveMode.java
@@ -18,28 +18,38 @@ package org.apache.spark.sql;
 
 /**
  * SaveMode is used to specify the expected behavior of saving a DataFrame to 
a data source.
+ *
+ * @since 1.3.0
  */
 public enum SaveMode {
   /**
    * Append mode means that when saving a DataFrame to a data source, if 
data/table already exists,
    * contents of the DataFrame are expected to be appended to existing data.
+   *
+   * @since 1.3.0
    */
   Append,
   /**
    * Overwrite mode means that when saving a DataFrame to a data source,
    * if data/table already exists, existing data is expected to be overwritten 
by the contents of
    * the DataFrame.
+   *
+   * @since 1.3.0
    */
   Overwrite,
   /**
    * ErrorIfExists mode means that when saving a DataFrame to a data source, 
if data already exists,
    * an exception is expected to be thrown.
+   *
+   * @since 1.3.0
    */
   ErrorIfExists,
   /**
    * Ignore mode means that when saving a DataFrame to a data source, if data 
already exists,
    * the save operation is expected to not save the contents of the DataFrame 
and to not
    * change the existing data.
+   *
+   * @since 1.3.0
    */
   Ignore
 }

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Column.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
index 4d50821..4773ded 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
@@ -45,6 +45,8 @@ private[sql] object Column {
  * @groupname expr_ops Expression operators.
  * @groupname df_ops DataFrame functions.
  * @groupname Ungrouped Support functions for DataFrames.
+ *
+ * @since 1.3.0
  */
 @Experimental
 class Column(protected[sql] val expr: Expression) extends Logging {
@@ -77,6 +79,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    *   of every struct in that array, and return an Array of fields
    *
    * @group expr_ops
+   * @since 1.4.0
    */
   def apply(extraction: Any): Column = UnresolvedExtractValue(expr, 
lit(extraction).expr)
 
@@ -92,6 +95,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def unary_- : Column = UnaryMinus(expr)
 
@@ -107,6 +111,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def unary_! : Column = Not(expr)
 
@@ -122,6 +127,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def === (other: Any): Column = {
     val right = lit(other).expr
@@ -145,6 +151,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def equalTo(other: Any): Column = this === other
 
@@ -161,6 +168,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def !== (other: Any): Column = Not(EqualTo(expr, lit(other).expr))
 
@@ -177,6 +185,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def notEqual(other: Any): Column = Not(EqualTo(expr, lit(other).expr))
 
@@ -192,6 +201,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def > (other: Any): Column = GreaterThan(expr, lit(other).expr)
 
@@ -207,6 +217,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def gt(other: Any): Column = this > other
 
@@ -221,6 +232,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def < (other: Any): Column = LessThan(expr, lit(other).expr)
 
@@ -235,6 +247,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def lt(other: Any): Column = this < other
 
@@ -249,6 +262,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def <= (other: Any): Column = LessThanOrEqual(expr, lit(other).expr)
 
@@ -263,6 +277,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def leq(other: Any): Column = this <= other
 
@@ -277,6 +292,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def >= (other: Any): Column = GreaterThanOrEqual(expr, lit(other).expr)
 
@@ -291,6 +307,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def geq(other: Any): Column = this >= other
 
@@ -298,6 +315,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * Equality test that is safe for null values.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def <=> (other: Any): Column = EqualNullSafe(expr, lit(other).expr)
 
@@ -305,6 +323,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * Equality test that is safe for null values.
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def eqNullSafe(other: Any): Column = this <=> other
 
@@ -312,6 +331,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * True if the current column is between the lower bound and upper bound, 
inclusive.
    *
    * @group java_expr_ops
+   * @since 1.4.0
    */
   def between(lowerBound: Any, upperBound: Any): Column = {
     (this >= lowerBound) && (this <= upperBound)
@@ -321,6 +341,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * True if the current expression is null.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def isNull: Column = IsNull(expr)
 
@@ -328,6 +349,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * True if the current expression is NOT null.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def isNotNull: Column = IsNotNull(expr)
 
@@ -342,6 +364,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def || (other: Any): Column = Or(expr, lit(other).expr)
 
@@ -356,6 +379,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def or(other: Column): Column = this || other
 
@@ -370,6 +394,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def && (other: Any): Column = And(expr, lit(other).expr)
 
@@ -384,6 +409,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def and(other: Column): Column = this && other
 
@@ -398,6 +424,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def + (other: Any): Column = Add(expr, lit(other).expr)
 
@@ -412,6 +439,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def plus(other: Any): Column = this + other
 
@@ -426,6 +454,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def - (other: Any): Column = Subtract(expr, lit(other).expr)
 
@@ -440,6 +469,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def minus(other: Any): Column = this - other
 
@@ -454,6 +484,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def * (other: Any): Column = Multiply(expr, lit(other).expr)
 
@@ -468,6 +499,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def multiply(other: Any): Column = this * other
 
@@ -482,6 +514,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def / (other: Any): Column = Divide(expr, lit(other).expr)
 
@@ -496,6 +529,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def divide(other: Any): Column = this / other
 
@@ -503,6 +537,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * Modulo (a.k.a. remainder) expression.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def % (other: Any): Column = Remainder(expr, lit(other).expr)
 
@@ -510,6 +545,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * Modulo (a.k.a. remainder) expression.
    *
    * @group java_expr_ops
+   * @since 1.3.0
    */
   def mod(other: Any): Column = this % other
 
@@ -518,6 +554,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * by the evaluated values of the arguments.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def in(list: Column*): Column = In(expr, list.map(_.expr))
@@ -526,6 +563,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * SQL like expression.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def like(literal: String): Column = Like(expr, lit(literal).expr)
 
@@ -533,6 +571,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * SQL RLIKE expression (LIKE with Regex).
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def rlike(literal: String): Column = RLike(expr, lit(literal).expr)
 
@@ -541,6 +580,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * or gets a value by key `key` in a [[MapType]].
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def getItem(key: Any): Column = UnresolvedExtractValue(expr, Literal(key))
 
@@ -548,6 +588,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * An expression that gets a field by name in a [[StructType]].
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def getField(fieldName: String): Column = UnresolvedExtractValue(expr, 
Literal(fieldName))
 
@@ -557,6 +598,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * @param len expression for the length of the substring.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def substr(startPos: Column, len: Column): Column = Substring(expr, 
startPos.expr, len.expr)
 
@@ -566,6 +608,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * @param len length of the substring.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def substr(startPos: Int, len: Int): Column = Substring(expr, 
lit(startPos).expr, lit(len).expr)
 
@@ -573,6 +616,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * Contains the other element.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def contains(other: Any): Column = Contains(expr, lit(other).expr)
 
@@ -580,6 +624,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * String starts with.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def startsWith(other: Column): Column = StartsWith(expr, lit(other).expr)
 
@@ -587,6 +632,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * String starts with another string literal.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def startsWith(literal: String): Column = this.startsWith(lit(literal))
 
@@ -594,6 +640,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * String ends with.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def endsWith(other: Column): Column = EndsWith(expr, lit(other).expr)
 
@@ -601,6 +648,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * String ends with another string literal.
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def endsWith(literal: String): Column = this.endsWith(lit(literal))
 
@@ -612,6 +660,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def as(alias: String): Column = Alias(expr, alias)()
 
@@ -623,6 +672,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def as(alias: Symbol): Column = Alias(expr, alias.name)()
 
@@ -634,6 +684,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def as(alias: String, metadata: Metadata): Column = {
     Alias(expr, alias)(explicitMetadata = Some(metadata))
@@ -651,6 +702,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def cast(to: DataType): Column = expr match {
     // Lift alias out of cast so we can support 
col.as("name").cast(IntegerType)
@@ -668,6 +720,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def cast(to: String): Column = cast(DataTypeParser.parse(to))
 
@@ -682,6 +735,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def desc: Column = SortOrder(expr, Descending)
 
@@ -696,6 +750,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.3.0
    */
   def asc: Column = SortOrder(expr, Ascending)
 
@@ -703,6 +758,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * Prints the expression to the console for debugging purpose.
    *
    * @group df_ops
+   * @since 1.3.0
    */
   def explain(extended: Boolean): Unit = {
     if (extended) {
@@ -719,6 +775,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.4.0
    */
   def bitwiseOR(other: Any): Column = BitwiseOr(expr, lit(other).expr)
 
@@ -729,6 +786,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.4.0
    */
   def bitwiseAND(other: Any): Column = BitwiseAnd(expr, lit(other).expr)
 
@@ -739,6 +797,7 @@ class Column(protected[sql] val expr: Expression) extends 
Logging {
    * }}}
    *
    * @group expr_ops
+   * @since 1.4.0
    */
   def bitwiseXOR(other: Any): Column = BitwiseXor(expr, lit(other).expr)
 
@@ -748,61 +807,115 @@ class Column(protected[sql] val expr: Expression) 
extends Logging {
 /**
  * :: Experimental ::
  * A convenient class used for constructing schema.
+ *
+ * @since 1.3.0
  */
 @Experimental
 class ColumnName(name: String) extends Column(name) {
 
-  /** Creates a new AttributeReference of type boolean */
+  /**
+   * Creates a new [[StructField]] of type boolean.
+   * @since 1.3.0
+   */
   def boolean: StructField = StructField(name, BooleanType)
 
-  /** Creates a new AttributeReference of type byte */
+  /**
+   * Creates a new [[StructField]] of type byte.
+   * @since 1.3.0
+   */
   def byte: StructField = StructField(name, ByteType)
 
-  /** Creates a new AttributeReference of type short */
+  /**
+   * Creates a new [[StructField]] of type short.
+   * @since 1.3.0
+   */
   def short: StructField = StructField(name, ShortType)
 
-  /** Creates a new AttributeReference of type int */
+  /**
+   * Creates a new [[StructField]] of type int.
+   * @since 1.3.0
+   */
   def int: StructField = StructField(name, IntegerType)
 
-  /** Creates a new AttributeReference of type long */
+  /**
+   * Creates a new [[StructField]] of type long.
+   * @since 1.3.0
+   */
   def long: StructField = StructField(name, LongType)
 
-  /** Creates a new AttributeReference of type float */
+  /**
+   * Creates a new [[StructField]] of type float.
+   * @since 1.3.0
+   */
   def float: StructField = StructField(name, FloatType)
 
-  /** Creates a new AttributeReference of type double */
+  /**
+   * Creates a new [[StructField]] of type double.
+   * @since 1.3.0
+   */
   def double: StructField = StructField(name, DoubleType)
 
-  /** Creates a new AttributeReference of type string */
+  /**
+   * Creates a new [[StructField]] of type string.
+   * @since 1.3.0
+   */
   def string: StructField = StructField(name, StringType)
 
-  /** Creates a new AttributeReference of type date */
+  /**
+   * Creates a new [[StructField]] of type date.
+   * @since 1.3.0
+   */
   def date: StructField = StructField(name, DateType)
 
-  /** Creates a new AttributeReference of type decimal */
+  /**
+   * Creates a new [[StructField]] of type decimal.
+   * @since 1.3.0
+   */
   def decimal: StructField = StructField(name, DecimalType.Unlimited)
 
-  /** Creates a new AttributeReference of type decimal */
+  /**
+   * Creates a new [[StructField]] of type decimal.
+   * @since 1.3.0
+   */
   def decimal(precision: Int, scale: Int): StructField =
     StructField(name, DecimalType(precision, scale))
 
-  /** Creates a new AttributeReference of type timestamp */
+  /**
+   * Creates a new [[StructField]] of type timestamp.
+   * @since 1.3.0
+   */
   def timestamp: StructField = StructField(name, TimestampType)
 
-  /** Creates a new AttributeReference of type binary */
+  /**
+   * Creates a new [[StructField]] of type binary.
+   * @since 1.3.0
+   */
   def binary: StructField = StructField(name, BinaryType)
 
-  /** Creates a new AttributeReference of type array */
+  /**
+   * Creates a new [[StructField]] of type array.
+   * @since 1.3.0
+   */
   def array(dataType: DataType): StructField = StructField(name, 
ArrayType(dataType))
 
-  /** Creates a new AttributeReference of type map */
+  /**
+   * Creates a new [[StructField]] of type map.
+   * @since 1.3.0
+   */
   def map(keyType: DataType, valueType: DataType): StructField =
     map(MapType(keyType, valueType))
 
   def map(mapType: MapType): StructField = StructField(name, mapType)
 
-  /** Creates a new AttributeReference of type struct */
+  /**
+   * Creates a new [[StructField]] of type struct.
+   * @since 1.3.0
+   */
   def struct(fields: StructField*): StructField = struct(StructType(fields))
 
+  /**
+   * Creates a new [[StructField]] of type struct.
+   * @since 1.3.0
+   */
   def struct(structType: StructType): StructField = StructField(name, 
structType)
 }

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
index 01fd432..c820a67 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
@@ -114,6 +114,7 @@ private[sql] object DataFrame {
  * @groupname rdd RDD Operations
  * @groupname output Output Operations
  * @groupname action Actions
+ * @since 1.3.0
  */
 // TODO: Improve documentation.
 @Experimental
@@ -233,6 +234,7 @@ class DataFrame private[sql](
   /**
    * Returns the object itself.
    * @group basic
+   * @since 1.3.0
    */
   // This is declared with parentheses to prevent the Scala compiler from 
treating
   // `rdd.toDF("1")` as invoking this toDF and then apply on the returned 
DataFrame.
@@ -247,6 +249,7 @@ class DataFrame private[sql](
    *   rdd.toDF("id", "name")  // this creates a DataFrame with column name 
"id" and "name"
    * }}}
    * @group basic
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def toDF(colNames: String*): DataFrame = {
@@ -264,12 +267,14 @@ class DataFrame private[sql](
   /**
    * Returns the schema of this [[DataFrame]].
    * @group basic
+   * @since 1.3.0
    */
   def schema: StructType = queryExecution.analyzed.schema
 
   /**
    * Returns all column names and their data types as an array.
    * @group basic
+   * @since 1.3.0
    */
   def dtypes: Array[(String, String)] = schema.fields.map { field =>
     (field.name, field.dataType.toString)
@@ -278,18 +283,21 @@ class DataFrame private[sql](
   /**
    * Returns all column names as an array.
    * @group basic
+   * @since 1.3.0
    */
   def columns: Array[String] = schema.fields.map(_.name)
 
   /**
    * Prints the schema to the console in a nice tree format.
    * @group basic
+   * @since 1.3.0
    */
   def printSchema(): Unit = println(schema.treeString)
 
   /**
    * Prints the plans (logical and physical) to the console for debugging 
purposes.
    * @group basic
+   * @since 1.3.0
    */
   def explain(extended: Boolean): Unit = {
     ExplainCommand(
@@ -302,6 +310,7 @@ class DataFrame private[sql](
   /**
    * Only prints the physical plan to the console for debugging purposes.
    * @group basic
+   * @since 1.3.0
    */
   def explain(): Unit = explain(extended = false)
 
@@ -309,6 +318,7 @@ class DataFrame private[sql](
    * Returns true if the `collect` and `take` methods can be run locally
    * (without any Spark executors).
    * @group basic
+   * @since 1.3.0
    */
   def isLocal: Boolean = logicalPlan.isInstanceOf[LocalRelation]
 
@@ -325,12 +335,14 @@ class DataFrame private[sql](
    * @param numRows Number of rows to show
    *
    * @group action
+   * @since 1.3.0
    */
   def show(numRows: Int): Unit = println(showString(numRows))
 
   /**
    * Displays the top 20 rows of [[DataFrame]] in a tabular form.
    * @group action
+   * @since 1.3.0
    */
   def show(): Unit = show(20)
 
@@ -342,6 +354,7 @@ class DataFrame private[sql](
    * }}}
    *
    * @group dfops
+   * @since 1.3.1
    */
   def na: DataFrameNaFunctions = new DataFrameNaFunctions(this)
 
@@ -353,6 +366,7 @@ class DataFrame private[sql](
    * }}}
    *
    * @group dfops
+   * @since 1.4.0
    */
   def stat: DataFrameStatFunctions = new DataFrameStatFunctions(this)
 
@@ -363,6 +377,7 @@ class DataFrame private[sql](
    *
    * @param right Right side of the join operation.
    * @group dfops
+   * @since 1.3.0
    */
   def join(right: DataFrame): DataFrame = {
     Join(logicalPlan, right.logicalPlan, joinType = Inner, None)
@@ -386,6 +401,7 @@ class DataFrame private[sql](
    * @param right Right side of the join operation.
    * @param usingColumn Name of the column to join on. This column must exist 
on both sides.
    * @group dfops
+   * @since 1.4.0
    */
   def join(right: DataFrame, usingColumn: String): DataFrame = {
     // Analyze the self join. The assumption is that the analyzer will 
disambiguate left vs right
@@ -416,6 +432,7 @@ class DataFrame private[sql](
    *   df1.join(df2).where($"df1Key" === $"df2Key")
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def join(right: DataFrame, joinExprs: Column): DataFrame = join(right, 
joinExprs, "inner")
 
@@ -437,6 +454,7 @@ class DataFrame private[sql](
    * @param joinExprs Join expression.
    * @param joinType One of: `inner`, `outer`, `left_outer`, `right_outer`, 
`leftsemi`.
    * @group dfops
+   * @since 1.3.0
    */
   def join(right: DataFrame, joinExprs: Column, joinType: String): DataFrame = 
{
     // Note that in this function, we introduce a hack in the case of 
self-join to automatically
@@ -483,6 +501,7 @@ class DataFrame private[sql](
    *   df.sort($"sortcol".asc)
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def sort(sortCol: String, sortCols: String*): DataFrame = {
@@ -495,6 +514,7 @@ class DataFrame private[sql](
    *   df.sort($"col1", $"col2".desc)
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def sort(sortExprs: Column*): DataFrame = {
@@ -513,6 +533,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] sorted by the given expressions.
    * This is an alias of the `sort` function.
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def orderBy(sortCol: String, sortCols: String*): DataFrame = sort(sortCol, 
sortCols :_*)
@@ -521,6 +542,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] sorted by the given expressions.
    * This is an alias of the `sort` function.
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def orderBy(sortExprs: Column*): DataFrame = sort(sortExprs :_*)
@@ -528,12 +550,14 @@ class DataFrame private[sql](
   /**
    * Selects column based on the column name and return it as a [[Column]].
    * @group dfops
+   * @since 1.3.0
    */
   def apply(colName: String): Column = col(colName)
 
   /**
    * Selects column based on the column name and return it as a [[Column]].
    * @group dfops
+   * @since 1.3.0
    */
   def col(colName: String): Column = colName match {
     case "*" =>
@@ -546,12 +570,14 @@ class DataFrame private[sql](
   /**
    * Returns a new [[DataFrame]] with an alias set.
    * @group dfops
+   * @since 1.3.0
    */
   def as(alias: String): DataFrame = Subquery(alias, logicalPlan)
 
   /**
    * (Scala-specific) Returns a new [[DataFrame]] with an alias set.
    * @group dfops
+   * @since 1.3.0
    */
   def as(alias: Symbol): DataFrame = as(alias.name)
 
@@ -561,6 +587,7 @@ class DataFrame private[sql](
    *   df.select($"colA", $"colB" + 1)
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def select(cols: Column*): DataFrame = {
@@ -583,6 +610,7 @@ class DataFrame private[sql](
    *   df.select($"colA", $"colB")
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def select(col: String, cols: String*): DataFrame = select((col +: 
cols).map(Column(_)) :_*)
@@ -595,6 +623,7 @@ class DataFrame private[sql](
    *   df.selectExpr("colA", "colB as newName", "abs(colC)")
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def selectExpr(exprs: String*): DataFrame = {
@@ -612,6 +641,7 @@ class DataFrame private[sql](
    *   peopleDf($"age" > 15)
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def filter(condition: Column): DataFrame = Filter(condition.expr, 
logicalPlan)
 
@@ -621,6 +651,7 @@ class DataFrame private[sql](
    *   peopleDf.filter("age > 15")
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def filter(conditionExpr: String): DataFrame = {
     filter(Column(new SqlParser().parseExpression(conditionExpr)))
@@ -635,6 +666,7 @@ class DataFrame private[sql](
    *   peopleDf($"age" > 15)
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def where(condition: Column): DataFrame = filter(condition)
 
@@ -653,6 +685,7 @@ class DataFrame private[sql](
    *   ))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def groupBy(cols: Column*): GroupedData = new GroupedData(this, 
cols.map(_.expr))
@@ -675,6 +708,7 @@ class DataFrame private[sql](
    *   ))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def groupBy(col1: String, cols: String*): GroupedData = {
@@ -690,6 +724,7 @@ class DataFrame private[sql](
    *   df.groupBy().agg("age" -> "max", "salary" -> "avg")
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def agg(aggExpr: (String, String), aggExprs: (String, String)*): DataFrame = 
{
     groupBy().agg(aggExpr, aggExprs :_*)
@@ -703,6 +738,7 @@ class DataFrame private[sql](
    *   df.groupBy().agg(Map("age" -> "max", "salary" -> "avg"))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def agg(exprs: Map[String, String]): DataFrame = groupBy().agg(exprs)
 
@@ -714,6 +750,7 @@ class DataFrame private[sql](
    *   df.groupBy().agg(Map("age" -> "max", "salary" -> "avg"))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def agg(exprs: java.util.Map[String, String]): DataFrame = 
groupBy().agg(exprs)
 
@@ -725,6 +762,7 @@ class DataFrame private[sql](
    *   df.groupBy().agg(max($"age"), avg($"salary"))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def agg(expr: Column, exprs: Column*): DataFrame = groupBy().agg(expr, exprs 
:_*)
@@ -733,6 +771,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] by taking the first `n` rows. The difference 
between this function
    * and `head` is that `head` returns an array while `limit` returns a new 
[[DataFrame]].
    * @group dfops
+   * @since 1.3.0
    */
   def limit(n: Int): DataFrame = Limit(Literal(n), logicalPlan)
 
@@ -740,6 +779,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] containing union of rows in this frame and 
another frame.
    * This is equivalent to `UNION ALL` in SQL.
    * @group dfops
+   * @since 1.3.0
    */
   def unionAll(other: DataFrame): DataFrame = Union(logicalPlan, 
other.logicalPlan)
 
@@ -747,6 +787,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] containing rows only in both this frame and 
another frame.
    * This is equivalent to `INTERSECT` in SQL.
    * @group dfops
+   * @since 1.3.0
    */
   def intersect(other: DataFrame): DataFrame = Intersect(logicalPlan, 
other.logicalPlan)
 
@@ -754,6 +795,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] containing rows in this frame but not in 
another frame.
    * This is equivalent to `EXCEPT` in SQL.
    * @group dfops
+   * @since 1.3.0
    */
   def except(other: DataFrame): DataFrame = Except(logicalPlan, 
other.logicalPlan)
 
@@ -764,6 +806,7 @@ class DataFrame private[sql](
    * @param fraction Fraction of rows to generate.
    * @param seed Seed for sampling.
    * @group dfops
+   * @since 1.3.0
    */
   def sample(withReplacement: Boolean, fraction: Double, seed: Long): 
DataFrame = {
     Sample(0.0, fraction, withReplacement, seed, logicalPlan)
@@ -775,6 +818,7 @@ class DataFrame private[sql](
    * @param withReplacement Sample with replacement or not.
    * @param fraction Fraction of rows to generate.
    * @group dfops
+   * @since 1.3.0
    */
   def sample(withReplacement: Boolean, fraction: Double): DataFrame = {
     sample(withReplacement, fraction, Utils.random.nextLong)
@@ -786,6 +830,7 @@ class DataFrame private[sql](
    * @param weights weights for splits, will be normalized if they don't sum 
to 1.
    * @param seed Seed for sampling.
    * @group dfops
+   * @since 1.4.0
    */
   def randomSplit(weights: Array[Double], seed: Long): Array[DataFrame] = {
     val sum = weights.sum
@@ -800,6 +845,7 @@ class DataFrame private[sql](
    *
    * @param weights weights for splits, will be normalized if they don't sum 
to 1.
    * @group dfops
+   * @since 1.4.0
    */
   def randomSplit(weights: Array[Double]): Array[DataFrame] = {
     randomSplit(weights, Utils.random.nextLong)
@@ -836,6 +882,7 @@ class DataFrame private[sql](
    *   val bookCountPerWord = 
allWords.groupBy("word").agg(countDistinct("title"))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def explode[A <: Product : TypeTag](input: Column*)(f: Row => 
TraversableOnce[A]): DataFrame = {
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
@@ -860,6 +907,7 @@ class DataFrame private[sql](
    *   df.explode("words", "word")(words: String => words.split(" "))
    * }}}
    * @group dfops
+   * @since 1.3.0
    */
   def explode[A, B : TypeTag](inputColumn: String, outputColumn: String)(f: A 
=> TraversableOnce[B])
     : DataFrame = {
@@ -883,6 +931,7 @@ class DataFrame private[sql](
   /**
    * Returns a new [[DataFrame]] by adding a column.
    * @group dfops
+   * @since 1.3.0
    */
   def withColumn(colName: String, col: Column): DataFrame = {
     val resolver = sqlContext.analyzer.resolver
@@ -902,6 +951,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] with a column renamed.
    * This is a no-op if schema doesn't contain existingName.
    * @group dfops
+   * @since 1.3.0
    */
   def withColumnRenamed(existingName: String, newName: String): DataFrame = {
     val resolver = sqlContext.analyzer.resolver
@@ -921,6 +971,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] with a column dropped.
    * This is a no-op if schema doesn't contain column name.
    * @group dfops
+   * @since 1.4.0
    */
   def drop(colName: String): DataFrame = {
     val resolver = sqlContext.analyzer.resolver
@@ -940,6 +991,7 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] that contains only the unique rows from this 
[[DataFrame]].
    * This is an alias for `distinct`.
    * @group dfops
+   * @since 1.4.0
    */
   def dropDuplicates(): DataFrame = dropDuplicates(this.columns)
 
@@ -948,6 +1000,7 @@ class DataFrame private[sql](
    * the subset of columns.
    *
    * @group dfops
+   * @since 1.4.0
    */
   def dropDuplicates(colNames: Seq[String]): DataFrame = {
     val groupCols = colNames.map(resolve)
@@ -967,6 +1020,7 @@ class DataFrame private[sql](
    * the subset of columns.
    *
    * @group dfops
+   * @since 1.4.0
    */
   def dropDuplicates(colNames: Array[String]): DataFrame = 
dropDuplicates(colNames.toSeq)
 
@@ -991,6 +1045,7 @@ class DataFrame private[sql](
    * }}}
    *
    * @group action
+   * @since 1.3.1
    */
   @scala.annotation.varargs
   def describe(cols: String*): DataFrame = {
@@ -1034,24 +1089,28 @@ class DataFrame private[sql](
   /**
    * Returns the first `n` rows.
    * @group action
+   * @since 1.3.0
    */
   def head(n: Int): Array[Row] = limit(n).collect()
 
   /**
    * Returns the first row.
    * @group action
+   * @since 1.3.0
    */
   def head(): Row = head(1).head
 
   /**
    * Returns the first row. Alias for head().
    * @group action
+   * @since 1.3.0
    */
   override def first(): Row = head()
 
   /**
    * Returns a new RDD by applying a function to all rows of this DataFrame.
    * @group rdd
+   * @since 1.3.0
    */
   override def map[R: ClassTag](f: Row => R): RDD[R] = rdd.map(f)
 
@@ -1059,12 +1118,14 @@ class DataFrame private[sql](
    * Returns a new RDD by first applying a function to all rows of this 
[[DataFrame]],
    * and then flattening the results.
    * @group rdd
+   * @since 1.3.0
    */
   override def flatMap[R: ClassTag](f: Row => TraversableOnce[R]): RDD[R] = 
rdd.flatMap(f)
 
   /**
    * Returns a new RDD by applying a function to each partition of this 
DataFrame.
    * @group rdd
+   * @since 1.3.0
    */
   override def mapPartitions[R: ClassTag](f: Iterator[Row] => Iterator[R]): 
RDD[R] = {
     rdd.mapPartitions(f)
@@ -1073,42 +1134,49 @@ class DataFrame private[sql](
   /**
    * Applies a function `f` to all rows.
    * @group rdd
+   * @since 1.3.0
    */
   override def foreach(f: Row => Unit): Unit = rdd.foreach(f)
 
   /**
    * Applies a function f to each partition of this [[DataFrame]].
    * @group rdd
+   * @since 1.3.0
    */
   override def foreachPartition(f: Iterator[Row] => Unit): Unit = 
rdd.foreachPartition(f)
 
   /**
    * Returns the first `n` rows in the [[DataFrame]].
    * @group action
+   * @since 1.3.0
    */
   override def take(n: Int): Array[Row] = head(n)
 
   /**
    * Returns an array that contains all of [[Row]]s in this [[DataFrame]].
    * @group action
+   * @since 1.3.0
    */
   override def collect(): Array[Row] = 
queryExecution.executedPlan.executeCollect()
 
   /**
    * Returns a Java list that contains all of [[Row]]s in this [[DataFrame]].
    * @group action
+   * @since 1.3.0
    */
   override def collectAsList(): java.util.List[Row] = 
java.util.Arrays.asList(rdd.collect() :_*)
 
   /**
    * Returns the number of rows in the [[DataFrame]].
    * @group action
+   * @since 1.3.0
    */
   override def count(): Long = groupBy().count().collect().head.getLong(0)
 
   /**
    * Returns a new [[DataFrame]] that has exactly `numPartitions` partitions.
    * @group rdd
+   * @since 1.3.0
    */
   override def repartition(numPartitions: Int): DataFrame = {
     Repartition(numPartitions, shuffle = true, logicalPlan)
@@ -1120,6 +1188,7 @@ class DataFrame private[sql](
    * if you go from 1000 partitions to 100 partitions, there will not be a 
shuffle, instead each of
    * the 100 new partitions will claim 10 of the current partitions.
    * @group rdd
+   * @since 1.4.0
    */
   override def coalesce(numPartitions: Int): DataFrame = {
     Repartition(numPartitions, shuffle = false, logicalPlan)
@@ -1129,11 +1198,13 @@ class DataFrame private[sql](
    * Returns a new [[DataFrame]] that contains only the unique rows from this 
[[DataFrame]].
    * This is an alias for `dropDuplicates`.
    * @group dfops
+   * @since 1.3.0
    */
   override def distinct: DataFrame = Distinct(logicalPlan)
 
   /**
    * @group basic
+   * @since 1.3.0
    */
   override def persist(): this.type = {
     sqlContext.cacheManager.cacheQuery(this)
@@ -1142,11 +1213,13 @@ class DataFrame private[sql](
 
   /**
    * @group basic
+   * @since 1.3.0
    */
   override def cache(): this.type = persist()
 
   /**
    * @group basic
+   * @since 1.3.0
    */
   override def persist(newLevel: StorageLevel): this.type = {
     sqlContext.cacheManager.cacheQuery(this, None, newLevel)
@@ -1155,6 +1228,7 @@ class DataFrame private[sql](
 
   /**
    * @group basic
+   * @since 1.3.0
    */
   override def unpersist(blocking: Boolean): this.type = {
     sqlContext.cacheManager.tryUncacheQuery(this, blocking)
@@ -1163,6 +1237,7 @@ class DataFrame private[sql](
 
   /**
    * @group basic
+   * @since 1.3.0
    */
   override def unpersist(): this.type = unpersist(blocking = false)
 
@@ -1175,6 +1250,7 @@ class DataFrame private[sql](
    * memoized. Once called, it won't change even if you change any query 
planning related Spark SQL
    * configurations (e.g. `spark.sql.shuffle.partitions`).
    * @group rdd
+   * @since 1.3.0
    */
   lazy val rdd: RDD[Row] = {
     // use a local variable to make sure the map closure doesn't capture the 
whole DataFrame
@@ -1188,12 +1264,14 @@ class DataFrame private[sql](
   /**
    * Returns the content of the [[DataFrame]] as a [[JavaRDD]] of [[Row]]s.
    * @group rdd
+   * @since 1.3.0
    */
   def toJavaRDD: JavaRDD[Row] = rdd.toJavaRDD()
 
   /**
    * Returns the content of the [[DataFrame]] as a [[JavaRDD]] of [[Row]]s.
    * @group rdd
+   * @since 1.3.0
    */
   def javaRDD: JavaRDD[Row] = toJavaRDD
 
@@ -1202,6 +1280,7 @@ class DataFrame private[sql](
    * temporary table is tied to the [[SQLContext]] that was used to create 
this DataFrame.
    *
    * @group basic
+   * @since 1.3.0
    */
   def registerTempTable(tableName: String): Unit = {
     sqlContext.registerDataFrameAsTable(this, tableName)
@@ -1212,6 +1291,7 @@ class DataFrame private[sql](
    * Files that are written out using this method can be read back in as a 
[[DataFrame]]
    * using the `parquetFile` function in [[SQLContext]].
    * @group output
+   * @since 1.3.0
    */
   def saveAsParquetFile(path: String): Unit = {
     if (sqlContext.conf.parquetUseDataSourceApi) {
@@ -1235,6 +1315,7 @@ class DataFrame private[sql](
    * Also note that while this function can persist the table metadata into 
Hive's metastore,
    * the table will NOT be accessible from Hive, until SPARK-7550 is resolved.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def saveAsTable(tableName: String): Unit = {
@@ -1254,6 +1335,7 @@ class DataFrame private[sql](
    * Also note that while this function can persist the table metadata into 
Hive's metastore,
    * the table will NOT be accessible from Hive, until SPARK-7550 is resolved.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def saveAsTable(tableName: String, mode: SaveMode): Unit = {
@@ -1281,6 +1363,7 @@ class DataFrame private[sql](
    * Also note that while this function can persist the table metadata into 
Hive's metastore,
    * the table will NOT be accessible from Hive, until SPARK-7550 is resolved.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def saveAsTable(tableName: String, source: String): Unit = {
@@ -1300,6 +1383,7 @@ class DataFrame private[sql](
    * Also note that while this function can persist the table metadata into 
Hive's metastore,
    * the table will NOT be accessible from Hive, until SPARK-7550 is resolved.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def saveAsTable(tableName: String, source: String, mode: SaveMode): Unit = {
@@ -1319,6 +1403,7 @@ class DataFrame private[sql](
    * Also note that while this function can persist the table metadata into 
Hive's metastore,
    * the table will NOT be accessible from Hive, until SPARK-7550 is resolved.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def saveAsTable(
@@ -1340,6 +1425,7 @@ class DataFrame private[sql](
    * an RDD out to a parquet file, and then register that file as a table.  
This "table" can then
    * be the target of an `insertInto`.
    * @group output
+   * @since 1.4.0
    */
   @Experimental
   def saveAsTable(
@@ -1365,6 +1451,7 @@ class DataFrame private[sql](
    * Also note that while this function can persist the table metadata into 
Hive's metastore,
    * the table will NOT be accessible from Hive, until SPARK-7550 is resolved.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def saveAsTable(
@@ -1396,6 +1483,7 @@ class DataFrame private[sql](
    * an RDD out to a parquet file, and then register that file as a table.  
This "table" can then
    * be the target of an `insertInto`.
    * @group output
+   * @since 1.4.0
    */
   @Experimental
   def saveAsTable(
@@ -1421,6 +1509,7 @@ class DataFrame private[sql](
    * using the default data source configured by spark.sql.sources.default and
    * [[SaveMode.ErrorIfExists]] as the save mode.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def save(path: String): Unit = {
@@ -1432,6 +1521,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame to the given path and [[SaveMode]] 
specified by mode,
    * using the default data source configured by spark.sql.sources.default.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def save(path: String, mode: SaveMode): Unit = {
@@ -1444,6 +1534,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame to the given path based on the given 
data source,
    * using [[SaveMode.ErrorIfExists]] as the save mode.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def save(path: String, source: String): Unit = {
@@ -1455,6 +1546,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame to the given path based on the given 
data source and
    * [[SaveMode]] specified by mode.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def save(path: String, source: String, mode: SaveMode): Unit = {
@@ -1466,6 +1558,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame based on the given data source,
    * [[SaveMode]] specified by mode, and a set of options.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def save(
@@ -1480,6 +1573,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame to the given path based on the given 
data source,
    * [[SaveMode]] specified by mode, and partition columns specified by 
`partitionColumns`.
    * @group output
+   * @since 1.4.0
    */
   @Experimental
   def save(
@@ -1496,6 +1590,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame based on the given data source,
    * [[SaveMode]] specified by mode, and a set of options
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def save(
@@ -1510,6 +1605,7 @@ class DataFrame private[sql](
    * Saves the contents of this DataFrame to the given path based on the given 
data source,
    * [[SaveMode]] specified by mode, and partition columns specified by 
`partitionColumns`.
    * @group output
+   * @since 1.4.0
    */
   @Experimental
   def save(
@@ -1524,6 +1620,7 @@ class DataFrame private[sql](
    * :: Experimental ::
    * Adds the rows from this RDD to the specified table, optionally 
overwriting the existing data.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def insertInto(tableName: String, overwrite: Boolean): Unit = {
@@ -1536,6 +1633,7 @@ class DataFrame private[sql](
    * Adds the rows from this RDD to the specified table.
    * Throws an exception if the table already exists.
    * @group output
+   * @since 1.3.0
    */
   @Experimental
   def insertInto(tableName: String): Unit = insertInto(tableName, overwrite = 
false)
@@ -1543,6 +1641,7 @@ class DataFrame private[sql](
   /**
    * Returns the content of the [[DataFrame]] as a RDD of JSON strings.
    * @group rdd
+   * @since 1.3.0
    */
   def toJSON: RDD[String] = {
     val rowSchema = this.schema
@@ -1581,6 +1680,7 @@ class DataFrame private[sql](
    * given name; if you pass `false`, it will throw if the table already
    * exists.
    * @group output
+   * @since 1.3.0
    */
   def createJDBCTable(url: String, table: String, allowExisting: Boolean): 
Unit = {
     createJDBCTable(url, table, allowExisting, new Properties())
@@ -1594,6 +1694,7 @@ class DataFrame private[sql](
    * given name; if you pass `false`, it will throw if the table already
    * exists.
    * @group output
+   * @since 1.4.0
    */
   def createJDBCTable(
       url: String,
@@ -1626,6 +1727,7 @@ class DataFrame private[sql](
    * the RDD in order via the simple statement
    * `INSERT INTO table VALUES (?, ?, ..., ?)` should not fail.
    * @group output
+   * @since 1.3.0
    */
   def insertIntoJDBC(url: String, table: String, overwrite: Boolean): Unit = {
     insertIntoJDBC(url, table, overwrite, new Properties())
@@ -1643,6 +1745,7 @@ class DataFrame private[sql](
    * the RDD in order via the simple statement
    * `INSERT INTO table VALUES (?, ?, ..., ?)` should not fail.
    * @group output
+   * @since 1.4.0
    */
   def insertIntoJDBC(
       url: String,

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
index a3187fe..b87efb5 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
@@ -19,6 +19,8 @@ package org.apache.spark.sql
 
 /**
  * A container for a [[DataFrame]], used for implicit conversions.
+ *
+ * @since 1.3.0
  */
 private[sql] case class DataFrameHolder(df: DataFrame) {
 

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
index 4a54120..b4c2daa 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
@@ -30,12 +30,16 @@ import org.apache.spark.sql.types._
 /**
  * :: Experimental ::
  * Functionality for working with missing data in [[DataFrame]]s.
+ *
+ * @since 1.3.1
  */
 @Experimental
 final class DataFrameNaFunctions private[sql](df: DataFrame) {
 
   /**
    * Returns a new [[DataFrame]] that drops rows containing any null values.
+   *
+   * @since 1.3.1
    */
   def drop(): DataFrame = drop("any", df.columns)
 
@@ -44,18 +48,24 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *
    * If `how` is "any", then drop rows containing any null values.
    * If `how` is "all", then drop rows only if every column is null for that 
row.
+   *
+   * @since 1.3.1
    */
   def drop(how: String): DataFrame = drop(how, df.columns)
 
   /**
    * Returns a new [[DataFrame]] that drops rows containing any null values
    * in the specified columns.
+   *
+   * @since 1.3.1
    */
   def drop(cols: Array[String]): DataFrame = drop(cols.toSeq)
 
   /**
    * (Scala-specific) Returns a new [[DataFrame ]] that drops rows containing 
any null values
    * in the specified columns.
+   *
+   * @since 1.3.1
    */
   def drop(cols: Seq[String]): DataFrame = drop(cols.size, cols)
 
@@ -65,6 +75,8 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
    *
    * If `how` is "any", then drop rows containing any null values in the 
specified columns.
    * If `how` is "all", then drop rows only if every specified column is null 
for that row.
+   *
+   * @since 1.3.1
    */
   def drop(how: String, cols: Array[String]): DataFrame = drop(how, cols.toSeq)
 
@@ -74,6 +86,8 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
    *
    * If `how` is "any", then drop rows containing any null values in the 
specified columns.
    * If `how` is "all", then drop rows only if every specified column is null 
for that row.
+   *
+   * @since 1.3.1
    */
   def drop(how: String, cols: Seq[String]): DataFrame = {
     how.toLowerCase match {
@@ -85,18 +99,24 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
 
   /**
    * Returns a new [[DataFrame]] that drops rows containing less than 
`minNonNulls` non-null values.
+   *
+   * @since 1.3.1
    */
   def drop(minNonNulls: Int): DataFrame = drop(minNonNulls, df.columns)
 
   /**
    * Returns a new [[DataFrame]] that drops rows containing less than 
`minNonNulls` non-null
    * values in the specified columns.
+   *
+   * @since 1.3.1
    */
   def drop(minNonNulls: Int, cols: Array[String]): DataFrame = 
drop(minNonNulls, cols.toSeq)
 
   /**
    * (Scala-specific) Returns a new [[DataFrame]] that drops rows containing 
less than
    * `minNonNulls` non-null values in the specified columns.
+   *
+   * @since 1.3.1
    */
   def drop(minNonNulls: Int, cols: Seq[String]): DataFrame = {
     // Filtering condition -- only keep the row if it has at least 
`minNonNulls` non-null values.
@@ -106,23 +126,31 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
 
   /**
    * Returns a new [[DataFrame]] that replaces null values in numeric columns 
with `value`.
+   *
+   * @since 1.3.1
    */
   def fill(value: Double): DataFrame = fill(value, df.columns)
 
   /**
    * Returns a new [[DataFrame ]] that replaces null values in string columns 
with `value`.
+   *
+   * @since 1.3.1
    */
   def fill(value: String): DataFrame = fill(value, df.columns)
 
   /**
    * Returns a new [[DataFrame]] that replaces null values in specified 
numeric columns.
    * If a specified column is not a numeric column, it is ignored.
+   *
+   * @since 1.3.1
    */
   def fill(value: Double, cols: Array[String]): DataFrame = fill(value, 
cols.toSeq)
 
   /**
    * (Scala-specific) Returns a new [[DataFrame]] that replaces null values in 
specified
    * numeric columns. If a specified column is not a numeric column, it is 
ignored.
+   *
+   * @since 1.3.1
    */
   def fill(value: Double, cols: Seq[String]): DataFrame = {
     val columnEquals = df.sqlContext.analyzer.resolver
@@ -140,12 +168,16 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
   /**
    * Returns a new [[DataFrame]] that replaces null values in specified string 
columns.
    * If a specified column is not a string column, it is ignored.
+   *
+   * @since 1.3.1
    */
   def fill(value: String, cols: Array[String]): DataFrame = fill(value, 
cols.toSeq)
 
   /**
    * (Scala-specific) Returns a new [[DataFrame]] that replaces null values in
    * specified string columns. If a specified column is not a string column, 
it is ignored.
+   *
+   * @since 1.3.1
    */
   def fill(value: String, cols: Seq[String]): DataFrame = {
     val columnEquals = df.sqlContext.analyzer.resolver
@@ -172,6 +204,8 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *   import com.google.common.collect.ImmutableMap;
    *   df.na.fill(ImmutableMap.of("A", "unknown", "B", 1.0));
    * }}}
+   *
+   * @since 1.3.1
    */
   def fill(valueMap: java.util.Map[String, Any]): DataFrame = 
fill0(valueMap.toSeq)
 
@@ -189,6 +223,8 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *     "B" -> 1.0
    *   ))
    * }}}
+   *
+   * @since 1.3.1
    */
   def fill(valueMap: Map[String, Any]): DataFrame = fill0(valueMap.toSeq)
 
@@ -212,6 +248,8 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *
    * @param col name of the column to apply the value replacement
    * @param replacement value replacement map, as explained above
+   *
+   * @since 1.3.1
    */
   def replace[T](col: String, replacement: java.util.Map[T, T]): DataFrame = {
     replace[T](col, replacement.toMap : Map[T, T])
@@ -233,6 +271,8 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *
    * @param cols list of columns to apply the value replacement
    * @param replacement value replacement map, as explained above
+   *
+   * @since 1.3.1
    */
   def replace[T](cols: Array[String], replacement: java.util.Map[T, T]): 
DataFrame = {
     replace(cols.toSeq, replacement.toMap)
@@ -256,6 +296,8 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *
    * @param col name of the column to apply the value replacement
    * @param replacement value replacement map, as explained above
+   *
+   * @since 1.3.1
    */
   def replace[T](col: String, replacement: Map[T, T]): DataFrame = {
     if (col == "*") {
@@ -279,6 +321,8 @@ final class DataFrameNaFunctions private[sql](df: 
DataFrame) {
    *
    * @param cols list of columns to apply the value replacement
    * @param replacement value replacement map, as explained above
+   *
+   * @since 1.3.1
    */
   def replace[T](cols: Seq[String], replacement: Map[T, T]): DataFrame = 
replace0(cols, replacement)
 

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
index a1e7447..5d106c1 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
@@ -23,6 +23,8 @@ import org.apache.spark.sql.execution.stat._
 /**
  * :: Experimental ::
  * Statistic functions for [[DataFrame]]s.
+ *
+ * @since 1.4.0
  */
 @Experimental
 final class DataFrameStatFunctions private[sql](df: DataFrame) {
@@ -32,6 +34,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    * @param col1 the name of the first column
    * @param col2 the name of the second column
    * @return the covariance of the two columns.
+   *
+   * @since 1.4.0
    */
   def cov(col1: String, col2: String): Double = {
     StatFunctions.calculateCov(df, Seq(col1, col2))
@@ -45,6 +49,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    * @param col1 the name of the column
    * @param col2 the name of the column to calculate the correlation against
    * @return The Pearson Correlation Coefficient as a Double.
+   *
+   * @since 1.4.0
    */
   def corr(col1: String, col2: String, method: String): Double = {
     require(method == "pearson", "Currently only the calculation of the 
Pearson Correlation " +
@@ -58,6 +64,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    * @param col1 the name of the column
    * @param col2 the name of the column to calculate the correlation against
    * @return The Pearson Correlation Coefficient as a Double.
+   *
+   * @since 1.4.0
    */
   def corr(col1: String, col2: String): Double = {
     corr(col1, col2, "pearson")
@@ -76,6 +84,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    * @param col2 The name of the second column. Distinct items will make the 
column names
    *             of the DataFrame.
    * @return A DataFrame containing for the contingency table.
+   *
+   * @since 1.4.0
    */
   def crosstab(col1: String, col2: String): DataFrame = {
     StatFunctions.crossTabulate(df, col1, col2)
@@ -91,6 +101,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    * @param support The minimum frequency for an item to be considered 
`frequent`. Should be greater
    *                than 1e-4.
    * @return A Local DataFrame with the Array of frequent items for each 
column.
+   *
+   * @since 1.4.0
    */
   def freqItems(cols: Array[String], support: Double): DataFrame = {
     FrequentItems.singlePassFreqItems(df, cols, support)
@@ -104,6 +116,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    *
    * @param cols the names of the columns to search frequent items in.
    * @return A Local DataFrame with the Array of frequent items for each 
column.
+   *
+   * @since 1.4.0
    */
   def freqItems(cols: Array[String]): DataFrame = {
     FrequentItems.singlePassFreqItems(df, cols, 0.01)
@@ -116,6 +130,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    *
    * @param cols the names of the columns to search frequent items in.
    * @return A Local DataFrame with the Array of frequent items for each 
column.
+   *
+   * @since 1.4.0
    */
   def freqItems(cols: Seq[String], support: Double): DataFrame = {
     FrequentItems.singlePassFreqItems(df, cols, support)
@@ -129,6 +145,8 @@ final class DataFrameStatFunctions private[sql](df: 
DataFrame) {
    *
    * @param cols the names of the columns to search frequent items in.
    * @return A Local DataFrame with the Array of frequent items for each 
column.
+   *
+   * @since 1.4.0
    */
   def freqItems(cols: Seq[String]): DataFrame = {
     FrequentItems.singlePassFreqItems(df, cols, 0.01)

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala
index d5d7e35..717709e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala
@@ -27,6 +27,8 @@ import org.apache.spark.annotation.Experimental
  * {{{
  *   sqlContext.experimental.extraStrategies += ...
  * }}}
+ *
+ * @since 1.3.0
  */
 @Experimental
 class ExperimentalMethods protected[sql](sqlContext: SQLContext) {
@@ -34,6 +36,8 @@ class ExperimentalMethods protected[sql](sqlContext: 
SQLContext) {
   /**
    * Allows extra strategies to be injected into the query planner at runtime. 
 Note this API
    * should be consider experimental and is not intended to be stable across 
releases.
+   *
+   * @since 1.3.0
    */
   @Experimental
   var extraStrategies: Seq[Strategy] = Nil

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
index 543320e..1381b9f 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
@@ -30,6 +30,8 @@ import org.apache.spark.sql.types.NumericType
 /**
  * :: Experimental ::
  * A set of methods for aggregations on a [[DataFrame]], created by 
[[DataFrame.groupBy]].
+ *
+ * @since 1.3.0
  */
 @Experimental
 class GroupedData protected[sql](df: DataFrame, groupingExprs: 
Seq[Expression]) {
@@ -94,6 +96,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    *     "expense" -> "sum"
    *   )
    * }}}
+   *
+   * @since 1.3.0
    */
   def agg(aggExpr: (String, String), aggExprs: (String, String)*): DataFrame = 
{
     agg((aggExpr +: aggExprs).toMap)
@@ -111,6 +115,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    *     "expense" -> "sum"
    *   ))
    * }}}
+   *
+   * @since 1.3.0
    */
   def agg(exprs: Map[String, String]): DataFrame = {
     exprs.map { case (colName, expr) =>
@@ -129,6 +135,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    *   import com.google.common.collect.ImmutableMap;
    *   df.groupBy("department").agg(ImmutableMap.of("age", "max", "expense", 
"sum"));
    * }}}
+   *
+   * @since 1.3.0
    */
   def agg(exprs: java.util.Map[String, String]): DataFrame = {
     agg(exprs.toMap)
@@ -162,6 +170,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    *   // Java, 1.3.x:
    *   df.groupBy("department").agg(col("department"), max("age"), 
sum("expense"));
    * }}}
+   *
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def agg(expr: Column, exprs: Column*): DataFrame = {
@@ -183,6 +193,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
   /**
    * Count the number of rows for each group.
    * The resulting [[DataFrame]] will also contain the grouping columns.
+   *
+   * @since 1.3.0
    */
   def count(): DataFrame = Seq(Alias(Count(Literal(1)), "count")())
 
@@ -190,6 +202,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    * Compute the average value for each numeric columns for each group. This 
is an alias for `avg`.
    * The resulting [[DataFrame]] will also contain the grouping columns.
    * When specified columns are given, only compute the average values for 
them.
+   *
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def mean(colNames: String*): DataFrame = {
@@ -200,6 +214,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    * Compute the max value for each numeric columns for each group.
    * The resulting [[DataFrame]] will also contain the grouping columns.
    * When specified columns are given, only compute the max values for them.
+   *
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def max(colNames: String*): DataFrame = {
@@ -210,6 +226,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    * Compute the mean value for each numeric columns for each group.
    * The resulting [[DataFrame]] will also contain the grouping columns.
    * When specified columns are given, only compute the mean values for them.
+   *
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def avg(colNames: String*): DataFrame = {
@@ -220,6 +238,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    * Compute the min value for each numeric column for each group.
    * The resulting [[DataFrame]] will also contain the grouping columns.
    * When specified columns are given, only compute the min values for them.
+   *
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def min(colNames: String*): DataFrame = {
@@ -230,6 +250,8 @@ class GroupedData protected[sql](df: DataFrame, 
groupingExprs: Seq[Expression])
    * Compute the sum for each numeric columns for each group.
    * The resulting [[DataFrame]] will also contain the grouping columns.
    * When specified columns are given, only compute the sum for them.
+   *
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def sum(colNames: String*): DataFrame = {

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/JavaTypeInference.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/JavaTypeInference.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/JavaTypeInference.scala
index db484c5..1ec874f 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/JavaTypeInference.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/JavaTypeInference.scala
@@ -21,11 +21,12 @@ import java.beans.Introspector
 import java.lang.{Iterable => JIterable}
 import java.util.{Iterator => JIterator, Map => JMap}
 
+import scala.language.existentials
+
 import com.google.common.reflect.TypeToken
 
 import org.apache.spark.sql.types._
 
-import scala.language.existentials
 
 /**
  * Type-inference utilities for POJOs and Java collections.

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
index 70ba898..975498c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
@@ -95,6 +95,8 @@ private[spark] class DefaultParserDialect extends 
ParserDialect {
  * @groupname config Configuration
  * @groupname dataframes Custom DataFrame Creation
  * @groupname Ungrouped Support functions for language integrated queries.
+ *
+ * @since 1.0.0
  */
 class SQLContext(@transient val sparkContext: SparkContext)
   extends org.apache.spark.Logging
@@ -113,6 +115,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Set Spark SQL configuration properties.
    *
    * @group config
+   * @since 1.0.0
    */
   def setConf(props: Properties): Unit = conf.setConf(props)
 
@@ -120,6 +123,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Set the given Spark SQL configuration property.
    *
    * @group config
+   * @since 1.0.0
    */
   def setConf(key: String, value: String): Unit = conf.setConf(key, value)
 
@@ -127,6 +131,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Return the value of Spark SQL configuration property for the given key.
    *
    * @group config
+   * @since 1.0.0
    */
   def getConf(key: String): String = conf.getConf(key)
 
@@ -135,6 +140,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * yet, return `defaultValue`.
    *
    * @group config
+   * @since 1.0.0
    */
   def getConf(key: String, defaultValue: String): String = conf.getConf(key, 
defaultValue)
 
@@ -143,6 +149,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * This creates a new copy of the config properties in the form of a Map.
    *
    * @group config
+   * @since 1.0.0
    */
   def getAllConfs: immutable.Map[String, String] = conf.getAllConfs
 
@@ -228,6 +235,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * the query planner for advanced functionality.
    *
    * @group basic
+   * @since 1.3.0
    */
   @Experimental
   @transient
@@ -238,6 +246,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Returns a [[DataFrame]] with no rows or columns.
    *
    * @group basic
+   * @since 1.3.0
    */
   @Experimental
   @transient
@@ -270,6 +279,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * }}}
    *
    * @group basic
+   * @since 1.3.0
    * TODO move to SQLSession?
    */
   @transient
@@ -278,23 +288,27 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
   /**
    * Returns true if the table is currently cached in-memory.
    * @group cachemgmt
+   * @since 1.3.0
    */
   def isCached(tableName: String): Boolean = cacheManager.isCached(tableName)
 
   /**
    * Caches the specified table in-memory.
    * @group cachemgmt
+   * @since 1.3.0
    */
   def cacheTable(tableName: String): Unit = cacheManager.cacheTable(tableName)
 
   /**
    * Removes the specified table from the in-memory cache.
    * @group cachemgmt
+   * @since 1.3.0
    */
   def uncacheTable(tableName: String): Unit = 
cacheManager.uncacheTable(tableName)
 
   /**
    * Removes all cached tables from the in-memory cache.
+   * @since 1.3.0
    */
   def clearCache(): Unit = cacheManager.clearCache()
 
@@ -311,27 +325,40 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * }}}
    *
    * @group basic
+   * @since 1.3.0
    */
   @Experimental
   object implicits extends Serializable {
     // scalastyle:on
 
-    /** Converts $"col name" into an [[Column]]. */
+    /**
+     * Converts $"col name" into an [[Column]].
+     * @since 1.3.0
+     */
     implicit class StringToColumn(val sc: StringContext) {
       def $(args: Any*): ColumnName = {
         new ColumnName(sc.s(args :_*))
       }
     }
 
-    /** An implicit conversion that turns a Scala `Symbol` into a [[Column]]. 
*/
+    /**
+     * An implicit conversion that turns a Scala `Symbol` into a [[Column]].
+     * @since 1.3.0
+     */
     implicit def symbolToColumn(s: Symbol): ColumnName = new ColumnName(s.name)
 
-    /** Creates a DataFrame from an RDD of case classes or tuples. */
+    /**
+     * Creates a DataFrame from an RDD of case classes or tuples.
+     * @since 1.3.0
+     */
     implicit def rddToDataFrameHolder[A <: Product : TypeTag](rdd: RDD[A]): 
DataFrameHolder = {
       DataFrameHolder(self.createDataFrame(rdd))
     }
 
-    /** Creates a DataFrame from a local Seq of Product. */
+    /**
+     * Creates a DataFrame from a local Seq of Product.
+     * @since 1.3.0
+     */
     implicit def localSeqToDataFrameHolder[A <: Product : TypeTag](data: 
Seq[A]): DataFrameHolder =
     {
       DataFrameHolder(self.createDataFrame(data))
@@ -341,7 +368,10 @@ class SQLContext(@transient val sparkContext: SparkContext)
     // making existing implicit conversions ambiguous. In particular, 
RDD[Double] is dangerous
     // because of [[DoubleRDDFunctions]].
 
-    /** Creates a single column DataFrame from an RDD[Int]. */
+    /**
+     * Creates a single column DataFrame from an RDD[Int].
+     * @since 1.3.0
+     */
     implicit def intRddToDataFrameHolder(data: RDD[Int]): DataFrameHolder = {
       val dataType = IntegerType
       val rows = data.mapPartitions { iter =>
@@ -354,7 +384,10 @@ class SQLContext(@transient val sparkContext: SparkContext)
       DataFrameHolder(self.createDataFrame(rows, StructType(StructField("_1", 
dataType) :: Nil)))
     }
 
-    /** Creates a single column DataFrame from an RDD[Long]. */
+    /**
+     * Creates a single column DataFrame from an RDD[Long].
+     * @since 1.3.0
+     */
     implicit def longRddToDataFrameHolder(data: RDD[Long]): DataFrameHolder = {
       val dataType = LongType
       val rows = data.mapPartitions { iter =>
@@ -367,7 +400,10 @@ class SQLContext(@transient val sparkContext: SparkContext)
       DataFrameHolder(self.createDataFrame(rows, StructType(StructField("_1", 
dataType) :: Nil)))
     }
 
-    /** Creates a single column DataFrame from an RDD[String]. */
+    /**
+     * Creates a single column DataFrame from an RDD[String].
+     * @since 1.3.0
+     */
     implicit def stringRddToDataFrameHolder(data: RDD[String]): 
DataFrameHolder = {
       val dataType = StringType
       val rows = data.mapPartitions { iter =>
@@ -386,6 +422,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Creates a DataFrame from an RDD of case classes.
    *
    * @group dataframes
+   * @since 1.3.0
    */
   @Experimental
   def createDataFrame[A <: Product : TypeTag](rdd: RDD[A]): DataFrame = {
@@ -401,6 +438,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Creates a DataFrame from a local Seq of Product.
    *
    * @group dataframes
+   * @since 1.3.0
    */
   @Experimental
   def createDataFrame[A <: Product : TypeTag](data: Seq[A]): DataFrame = {
@@ -414,6 +452,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Convert a [[BaseRelation]] created for external data sources into a 
[[DataFrame]].
    *
    * @group dataframes
+   * @since 1.3.0
    */
   def baseRelationToDataFrame(baseRelation: BaseRelation): DataFrame = {
     DataFrame(this, LogicalRelation(baseRelation))
@@ -449,6 +488,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * }}}
    *
    * @group dataframes
+   * @since 1.3.0
    */
   @DeveloperApi
   def createDataFrame(rowRDD: RDD[Row], schema: StructType): DataFrame = {
@@ -480,6 +520,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * the provided schema. Otherwise, there will be runtime exception.
    *
    * @group dataframes
+   * @since 1.3.0
    */
   @DeveloperApi
   def createDataFrame(rowRDD: JavaRDD[Row], schema: StructType): DataFrame = {
@@ -492,6 +533,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * WARNING: Since there is no guaranteed ordering for fields in a Java Bean,
    *          SELECT * queries will return the columns in an undefined order.
    * @group dataframes
+   * @since 1.3.0
    */
   def createDataFrame(rdd: RDD[_], beanClass: Class[_]): DataFrame = {
     val attributeSeq = getSchema(beanClass)
@@ -520,6 +562,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * WARNING: Since there is no guaranteed ordering for fields in a Java Bean,
    *          SELECT * queries will return the columns in an undefined order.
    * @group dataframes
+   * @since 1.3.0
    */
   def createDataFrame(rdd: JavaRDD[_], beanClass: Class[_]): DataFrame = {
     createDataFrame(rdd.rdd, beanClass)
@@ -591,6 +634,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * [[DataFrame]] if no paths are passed in.
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @scala.annotation.varargs
   def parquetFile(paths: String*): DataFrame = {
@@ -609,6 +653,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * It goes through the entire dataset once to determine the schema.
    *
    * @group specificdata
+   * @since 1.3.0
    */
   def jsonFile(path: String): DataFrame = jsonFile(path, 1.0)
 
@@ -618,6 +663,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * returning the result as a [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jsonFile(path: String, schema: StructType): DataFrame =
@@ -626,6 +672,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
   /**
    * :: Experimental ::
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jsonFile(path: String, samplingRatio: Double): DataFrame =
@@ -637,6 +684,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * It goes through the entire dataset once to determine the schema.
    *
    * @group specificdata
+   * @since 1.3.0
    */
   def jsonRDD(json: RDD[String]): DataFrame = jsonRDD(json, 1.0)
 
@@ -647,6 +695,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * It goes through the entire dataset once to determine the schema.
    *
    * @group specificdata
+   * @since 1.3.0
    */
   def jsonRDD(json: JavaRDD[String]): DataFrame = jsonRDD(json.rdd, 1.0)
 
@@ -656,6 +705,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * returning the result as a [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jsonRDD(json: RDD[String], schema: StructType): DataFrame = {
@@ -678,6 +728,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * schema, returning the result as a [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jsonRDD(json: JavaRDD[String], schema: StructType): DataFrame = {
@@ -690,6 +741,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * schema, returning the result as a [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jsonRDD(json: RDD[String], samplingRatio: Double): DataFrame = {
@@ -711,6 +763,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * schema, returning the result as a [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jsonRDD(json: JavaRDD[String], samplingRatio: Double): DataFrame = {
@@ -723,6 +776,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * using the default data source configured by spark.sql.sources.default.
    *
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(path: String): DataFrame = {
@@ -735,6 +789,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Returns the dataset stored at path as a DataFrame, using the given data 
source.
    *
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(path: String, source: String): DataFrame = {
@@ -747,6 +802,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * a set of options as a DataFrame.
    *
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(source: String, options: java.util.Map[String, String]): DataFrame 
= {
@@ -759,6 +815,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * a set of options as a DataFrame.
    *
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(source: String, options: Map[String, String]): DataFrame = {
@@ -772,6 +829,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * a set of options as a DataFrame, using the given schema as the schema of 
the DataFrame.
    *
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(
@@ -787,6 +845,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * a set of options as a DataFrame, using the given schema as the schema of 
the DataFrame.
    *
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(
@@ -802,6 +861,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * (Scala-specific) Returns the dataset specified by the given data source 
and
    * a set of options as a DataFrame, using the given schema as the schema of 
the DataFrame.
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(
@@ -817,6 +877,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * (Scala-specific) Returns the dataset specified by the given data source 
and
    * a set of options as a DataFrame, using the given schema as the schema of 
the DataFrame.
    * @group genericdata
+   * @since 1.3.0
    */
   @Experimental
   def load(
@@ -834,6 +895,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * It will use the default data source configured by 
spark.sql.sources.default.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   @Experimental
   def createExternalTable(tableName: String, path: String): DataFrame = {
@@ -847,6 +909,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * and returns the corresponding DataFrame.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   @Experimental
   def createExternalTable(
@@ -862,6 +925,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Then, returns the corresponding DataFrame.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   @Experimental
   def createExternalTable(
@@ -878,6 +942,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * Then, returns the corresponding DataFrame.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   @Experimental
   def createExternalTable(
@@ -903,6 +968,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * a set of options. Then, returns the corresponding DataFrame.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   @Experimental
   def createExternalTable(
@@ -920,6 +986,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * a set of options. Then, returns the corresponding DataFrame.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   @Experimental
   def createExternalTable(
@@ -946,6 +1013,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * url named table.
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jdbc(url: String, table: String): DataFrame = {
@@ -958,6 +1026,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * url named table and connection properties.
    *
    * @group specificdata
+   * @since 1.4.0
    */
   @Experimental
   def jdbc(url: String, table: String, properties: Properties): DataFrame = {
@@ -976,6 +1045,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * @param numPartitions the number of partitions.  the range 
`minValue`-`maxValue` will be split
    *                      evenly into this many partitions
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jdbc(
@@ -1001,6 +1071,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    *                      evenly into this many partitions
    * @param properties connection properties
    * @group specificdata
+   * @since 1.4.0
    */
   @Experimental
   def jdbc(
@@ -1024,6 +1095,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * of the [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.3.0
    */
   @Experimental
   def jdbc(url: String, table: String, theParts: Array[String]): DataFrame = {
@@ -1038,6 +1110,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * of the [[DataFrame]].
    *
    * @group specificdata
+   * @since 1.4.0
    */
   @Experimental
   def jdbc(
@@ -1075,6 +1148,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * @param tableName the name of the table to be unregistered.
    *
    * @group basic
+   * @since 1.3.0
    */
   def dropTempTable(tableName: String): Unit = {
     cacheManager.tryUncacheQuery(table(tableName))
@@ -1086,6 +1160,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * used for SQL parsing can be configured with 'spark.sql.dialect'.
    *
    * @group basic
+   * @since 1.3.0
    */
   def sql(sqlText: String): DataFrame = {
     DataFrame(this, parseSql(sqlText))
@@ -1095,6 +1170,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * Returns the specified table as a [[DataFrame]].
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   def table(tableName: String): DataFrame =
     DataFrame(this, catalog.lookupRelation(Seq(tableName)))
@@ -1105,6 +1181,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * indicating if a table is a temporary one or not).
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   def tables(): DataFrame = {
     DataFrame(this, ShowTablesCommand(None))
@@ -1116,6 +1193,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * indicating if a table is a temporary one or not).
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   def tables(databaseName: String): DataFrame = {
     DataFrame(this, ShowTablesCommand(Some(databaseName)))
@@ -1125,6 +1203,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * Returns the names of tables in the current database as an array.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   def tableNames(): Array[String] = {
     catalog.getTables(None).map {
@@ -1136,6 +1215,7 @@ class SQLContext(@transient val sparkContext: 
SparkContext)
    * Returns the names of tables in the given database as an array.
    *
    * @group ddl_ops
+   * @since 1.3.0
    */
   def tableNames(databaseName: String): Array[String] = {
     catalog.getTables(Some(databaseName)).map {

http://git-wip-us.apache.org/repos/asf/spark/blob/bdd5db9f/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala
index 5921eaf..6b1ae81 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala
@@ -17,7 +17,6 @@
 
 package org.apache.spark.sql
 
-
 import scala.util.parsing.combinator.RegexParsers
 
 import org.apache.spark.sql.catalyst.AbstractSparkSQLParser


---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org
For additional commands, e-mail: commits-h...@spark.apache.org