From e71141d295d18d2a3937f6c3193d8fa7805b59b9 Mon Sep 17 00:00:00 2001
From: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Date: Wed, 9 Sep 2015 15:34:34 +0900
Subject: [PATCH 1/2] [SPARK-10275][MLlib] Add @since annotation to
 pyspark.mllib.random

---
 python/pyspark/mllib/random.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/python/pyspark/mllib/random.py b/python/pyspark/mllib/random.py
index 06fbc0eb6aef0..34626c3a5078c 100644
--- a/python/pyspark/mllib/random.py
+++ b/python/pyspark/mllib/random.py
@@ -21,6 +21,7 @@
 
 from functools import wraps
 
+from pyspark import since
 from pyspark.mllib.common import callMLlibFunc
 
 
@@ -42,6 +43,7 @@ class RandomRDDs(object):
     """
 
     @staticmethod
+    @since("1.1.0")
     def uniformRDD(sc, size, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of i.i.d. samples from the
@@ -72,6 +74,7 @@ def uniformRDD(sc, size, numPartitions=None, seed=None):
         return callMLlibFunc("uniformRDD", sc._jsc, size, numPartitions, seed)
 
     @staticmethod
+    @since("1.1.0")
     def normalRDD(sc, size, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of i.i.d. samples from the standard normal
@@ -100,6 +103,7 @@ def normalRDD(sc, size, numPartitions=None, seed=None):
         return callMLlibFunc("normalRDD", sc._jsc, size, numPartitions, seed)
 
     @staticmethod
+    @since("1.3.0")
     def logNormalRDD(sc, mean, std, size, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of i.i.d. samples from the log normal
@@ -132,6 +136,7 @@ def logNormalRDD(sc, mean, std, size, numPartitions=None, seed=None):
                              size, numPartitions, seed)
 
     @staticmethod
+    @since("1.1.0")
     def poissonRDD(sc, mean, size, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of i.i.d. samples from the Poisson
@@ -158,6 +163,7 @@ def poissonRDD(sc, mean, size, numPartitions=None, seed=None):
         return callMLlibFunc("poissonRDD", sc._jsc, float(mean), size, numPartitions, seed)
 
     @staticmethod
+    @since("1.3.0")
     def exponentialRDD(sc, mean, size, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of i.i.d. samples from the Exponential
@@ -184,6 +190,7 @@ def exponentialRDD(sc, mean, size, numPartitions=None, seed=None):
         return callMLlibFunc("exponentialRDD", sc._jsc, float(mean), size, numPartitions, seed)
 
     @staticmethod
+    @since("1.3.0")
     def gammaRDD(sc, shape, scale, size, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of i.i.d. samples from the Gamma
@@ -216,6 +223,7 @@ def gammaRDD(sc, shape, scale, size, numPartitions=None, seed=None):
 
     @staticmethod
     @toArray
+    @since("1.1.0")
     def uniformVectorRDD(sc, numRows, numCols, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of vectors containing i.i.d. samples drawn
@@ -241,6 +249,7 @@ def uniformVectorRDD(sc, numRows, numCols, numPartitions=None, seed=None):
 
     @staticmethod
     @toArray
+    @since("1.1.0")
     def normalVectorRDD(sc, numRows, numCols, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of vectors containing i.i.d. samples drawn
@@ -266,6 +275,7 @@ def normalVectorRDD(sc, numRows, numCols, numPartitions=None, seed=None):
 
     @staticmethod
     @toArray
+    @since("1.3.0")
     def logNormalVectorRDD(sc, mean, std, numRows, numCols, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of vectors containing i.i.d. samples drawn
@@ -300,6 +310,7 @@ def logNormalVectorRDD(sc, mean, std, numRows, numCols, numPartitions=None, seed
 
     @staticmethod
     @toArray
+    @since("1.1.0")
     def poissonVectorRDD(sc, mean, numRows, numCols, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of vectors containing i.i.d. samples drawn
@@ -330,6 +341,7 @@ def poissonVectorRDD(sc, mean, numRows, numCols, numPartitions=None, seed=None):
 
     @staticmethod
     @toArray
+    @since("1.3.0")
     def exponentialVectorRDD(sc, mean, numRows, numCols, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of vectors containing i.i.d. samples drawn
@@ -360,6 +372,7 @@ def exponentialVectorRDD(sc, mean, numRows, numCols, numPartitions=None, seed=No
 
     @staticmethod
     @toArray
+    @since("1.3.0")
     def gammaVectorRDD(sc, shape, scale, numRows, numCols, numPartitions=None, seed=None):
         """
         Generates an RDD comprised of vectors containing i.i.d. samples drawn

From 6a8817ba60d30af372a93e2171e3a7add15f374d Mon Sep 17 00:00:00 2001
From: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Date: Thu, 10 Sep 2015 11:18:40 +0900
Subject: [PATCH 2/2] Add a since version comment to RandomRDDs manually

---
 python/pyspark/mllib/random.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/python/pyspark/mllib/random.py b/python/pyspark/mllib/random.py
index 34626c3a5078c..9c733b1332bc0 100644
--- a/python/pyspark/mllib/random.py
+++ b/python/pyspark/mllib/random.py
@@ -40,6 +40,8 @@ class RandomRDDs(object):
     """
     Generator methods for creating RDDs comprised of i.i.d samples from
     some distribution.
+
+    .. addedversion:: 1.1.0
     """
 
     @staticmethod