addressed reviewer comments

Author: dorx

core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala

@@ -212,18 +212,15 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
       exact: Boolean = true,
       seed: Long = Utils.random.nextLong): RDD[(K, V)]= {
 
-    require(fractions.forall({case(k, v) => v >= 0.0}), "Invalid sampling rates.")
+    require(fractions.forall {case(k, v) => v >= 0.0}, "Invalid sampling rates.")
 
-    if (withReplacement) {
+    val samplingFunc = if (withReplacement) {
       val counts = if (exact) Some(this.countByKey()) else None
-      val samplingFunc =
         StratifiedSampler.getPoissonSamplingFunction(self, fractions, exact, counts, seed)
-      self.mapPartitionsWithIndex(samplingFunc, preservesPartitioning = true)
     } else {
-      val samplingFunc =
         StratifiedSampler.getBernoulliSamplingFunction(self, fractions, exact, seed)
-      self.mapPartitionsWithIndex(samplingFunc, preservesPartitioning = true)
     }
+    self.mapPartitionsWithIndex(samplingFunc, preservesPartitioning=true)
   }
 
   /**

core/src/main/scala/org/apache/spark/rdd/RDD.scala

@@ -350,7 +350,6 @@ abstract class RDD[T: ClassTag](
 
   /**
    * Return a sampled subset of this RDD.
-   *
    */
   def sample(withReplacement: Boolean, 
       fraction: Double, 

core/src/main/scala/org/apache/spark/util/random/SamplingUtils.scala

@@ -72,6 +72,7 @@ private[spark] object SamplingUtils {
 private[spark] object PoissonBounds {
 
   val delta = 1e-4 / 3.0
+  val epsilon = 1e-15
 
   /**
    * Compute the threshold for accepting items on the fly. The threshold value is a fairly small
@@ -87,7 +88,7 @@ private[spark] object PoissonBounds {
     var ub = s
     while (lb < ub - 1.0) {
       val m = (lb + ub) / 2.0
-      val poisson = new PoissonDistribution(m, 1e-15)
+      val poisson = new PoissonDistribution(m, epsilon)
       val y = poisson.inverseCumulativeProbability(1 - delta)
       if (y > s) ub = m else lb = m
     }
@@ -96,7 +97,7 @@ private[spark] object PoissonBounds {
 
   def getMinCount(lmbd: Double): Double = {
     if (lmbd == 0) return 0
-    val poisson = new PoissonDistribution(lmbd, 1e-15)
+    val poisson = new PoissonDistribution(lmbd, epsilon)
     poisson.inverseCumulativeProbability(delta)
   }
 
@@ -114,7 +115,7 @@ private[spark] object PoissonBounds {
     var ub = s + math.sqrt(s / delta) // Chebyshev's inequality
     while (lb < ub - 1.0) {
       val m = (lb + ub) / 2.0
-      val poisson = new PoissonDistribution(m, 1e-15)
+      val poisson = new PoissonDistribution(m, epsilon)
       val y = poisson.inverseCumulativeProbability(delta)
       if (y >= s) ub = m else lb = m
     }