Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/2928#discussion_r19362102
--- Diff: core/src/main/scala/org/apache/spark/rdd/SampledRDD.scala ---
@@ -53,9 +53,14 @@ private[spark] class SampledRDD[T: ClassTag](
if (withReplacement) {
// For large datasets, the expected number of occurrences of each
element in a sample with
// replacement is Poisson(frac). We use that to get a count for each
element.
- val poisson = new Poisson(frac, new DRand(split.seed))
+ val poisson = new PoissonDistribution(
+ new MersenneTwister(split.seed),
--- End diff --
The default RNG is Well19937c. From the doc, it is better but slower than
MT. I'm leaning towards the default because sampling computation is usually not
the bottleneck for Spark.
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