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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