switch to python implementation

Author: Davies Liu

core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala

@@ -758,13 +758,6 @@ private[spark] object PythonRDD extends Logging {
       converted.saveAsHadoopDataset(new JobConf(conf))
     }
   }
-
-  /**
-   * A helper to convert java.util.List[Double] into Array[Double]
-   */
-  def listToArrayDouble(list: JList[Double]): Array[Double] = {
-    list.asScala.toArray
-  }
 }
 
 private

python/pyspark/rdd.py

@@ -28,7 +28,7 @@
 import warnings
 import heapq
 import bisect
-from random import Random
+import random
 from math import sqrt, log, isinf, isnan
 
 from pyspark.accumulators import PStatsParam
@@ -324,25 +324,21 @@ def randomSplit(self, weights, seed=None):
         :param seed: random seed
         :return: split RDDs in a list
 
-        >>> rdd = sc.parallelize(range(10), 1)
-        >>> rdd1, rdd2, rdd3 = rdd.randomSplit([0.4, 0.6, 1.0], 11)
+        >>> rdd = sc.parallelize(range(5), 1)
+        >>> rdd1, rdd2 = rdd.randomSplit([2.0, 3.0], 101)
         >>> rdd1.collect()
-        [3, 6]
+        [2, 3]
         >>> rdd2.collect()
-        [0, 5, 7]
-        >>> rdd3.collect()
-        [1, 2, 4, 8, 9]
+        [0, 1, 4]
         """
-        ser = BatchedSerializer(PickleSerializer(), 1)
-        rdd = self._reserialize(ser)
-        jweights = ListConverter().convert([float(w) for w in weights],
-                                           self.ctx._gateway._gateway_client)
-        jweights = self.ctx._jvm.PythonRDD.listToArrayDouble(jweights)
+        s = sum(weights)
+        cweights = [0.0]
+        for w in weights:
+            cweights.append(cweights[-1] + w / s)
         if seed is None:
-            jrdds = rdd._jrdd.randomSplit(jweights)
-        else:
-            jrdds = rdd._jrdd.randomSplit(jweights, seed)
-        return [RDD(jrdd, self.ctx, ser) for jrdd in jrdds]
+            seed = random.randint(0, 2 ** 32 - 1)
+        return [self.mapPartitionsWithIndex(RDDSampler(False, ub, seed, lb).func, True)
+                for lb, ub in zip(cweights, cweights[1:])]
 
     # this is ported from scala/spark/RDD.scala
     def takeSample(self, withReplacement, num, seed=None):
@@ -369,7 +365,7 @@ def takeSample(self, withReplacement, num, seed=None):
         if initialCount == 0:
             return []
 
-        rand = Random(seed)
+        rand = random.Random(seed)
 
         if (not withReplacement) and num >= initialCount:
             # shuffle current RDD and return

python/pyspark/rddsampler.py

@@ -96,9 +96,10 @@ def shuffle(self, vals):
 
 class RDDSampler(RDDSamplerBase):
 
-    def __init__(self, withReplacement, fraction, seed=None):
+    def __init__(self, withReplacement, fraction, seed=None, lowbound=0.0):
         RDDSamplerBase.__init__(self, withReplacement, seed)
         self._fraction = fraction
+        self._lowbound = lowbound
 
     def func(self, split, iterator):
         if self._withReplacement:
@@ -111,7 +112,7 @@ def func(self, split, iterator):
                     yield obj
         else:
             for obj in iterator:
-                if self.getUniformSample(split) <= self._fraction:
+                if self._lowbound <= self.getUniformSample(split) < self._fraction:
                     yield obj