Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11981#discussion_r57520944
--- Diff: core/src/main/scala/org/apache/spark/partial/SumEvaluator.scala
---
@@ -42,6 +42,14 @@ private[spark] class SumEvaluator(totalOutputs: Int,
confidence: Double)
new BoundedDouble(counter.sum, 1.0, counter.sum, counter.sum)
} else if (outputsMerged == 0) {
new BoundedDouble(0, 0.0, Double.NegativeInfinity,
Double.PositiveInfinity)
+ } else if (counter.count == 0) {
+ new BoundedDouble(0, 0.0, Double.NegativeInfinity,
Double.PositiveInfinity)
+ } else if (counter.count == 1) {
+ val p = outputsMerged.toDouble / totalOutputs
--- End diff --
This duplicates code in the following block. I think you can compute the
common values in one shared block and then branch afterwards to handle count ==
1.
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