Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/13260#discussion_r64337732
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -550,17 +550,19 @@ abstract class RDD[T: ClassTag](
} else {
val fraction = SamplingUtils.computeFractionForSampleSize(num,
initialCount,
withReplacement)
- var samples = this.sample(withReplacement, fraction,
rand.nextInt()).collect()
+ var samples = this.sample(withReplacement, fraction,
rand.nextInt())
+ var count = samples.count()
// If the first sample didn't turn out large enough, keep trying
to take samples;
// this shouldn't happen often because we use a big multiplier
for the initial size
var numIters = 0
- while (samples.length < num) {
+ while (count < num) {
logWarning(s"Needed to re-sample due to insufficient sample
size. Repeat #$numIters")
- samples = this.sample(withReplacement, fraction,
rand.nextInt()).collect()
+ samples = this.sample(withReplacement, fraction,
rand.nextInt())
+ count = samples.count()
numIters += 1
}
- Utils.randomizeInPlace(samples, rand).take(num)
+ Utils.randomizeInPlace(samples.collect(), rand).take(num)
--- End diff --
I think it's important to not have regressions. These samples might be
large, in which case it's worth using a little more memory than doing another
pass.
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