Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/16497#discussion_r95297609
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Percentile.scala
---
@@ -126,10 +152,15 @@ case class Percentile(
buffer: OpenHashMap[Number, Long],
input: InternalRow): OpenHashMap[Number, Long] = {
val key = child.eval(input).asInstanceOf[Number]
+ val frqValue = frequency.eval(input)
// Null values are ignored in counts map.
- if (key != null) {
- buffer.changeValue(key, 1L, _ + 1L)
+ if (key != null && frqValue != null) {
--- End diff --
I don't think we should default to 1L as a value. That seems more wrong
than either failing or skipping.
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