Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11982#discussion_r57529477
--- Diff: core/src/main/scala/org/apache/spark/partial/SumEvaluator.scala
---
@@ -56,9 +56,12 @@ private[spark] class SumEvaluator(totalOutputs: Int,
confidence: Double)
val confFactor = {
if (counter.count > 100) {
new NormalDistribution().inverseCumulativeProbability(1 - (1 -
confidence) / 2)
- } else {
+ } else if (counter.count > 1) {
val degreesOfFreedom = (counter.count - 1).toInt
new
TDistribution(degreesOfFreedom).inverseCumulativeProbability(1 - (1 -
confidence) / 2)
+ } else {
+ // No way to meaningfully estimate confidence, so we signal no
particular confidence interval
+ Double.PositiveInfinity
--- End diff --
But the relevant computation is:
```
scala> Double.NaN * Double.PositiveInfinity
res1: Double = NaN
```
The interval should not be `NaN`.
If count is 1 then the sample variance is NaN along with everything else
that's a function of a second moment.
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