Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/18113#discussion_r118838177
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/typedaggregators.scala
---
@@ -99,3 +97,67 @@ class TypedAverage[IN](val f: IN => Double) extends
Aggregator[IN, (Double, Long
toColumn.asInstanceOf[TypedColumn[IN, java.lang.Double]]
}
}
+
+class TypedMinDouble[IN](val f: IN => Double) extends Aggregator[IN,
Double, Double] {
+ override def zero: Double = Double.PositiveInfinity
--- End diff --
Currently seems the behavior of aggregation expressions is more reasonable.
I am not sure that if we consider this corner case when we implement those
aggregators.
It seems to me that we can fix this inconsistency by just modifying those
aggregators. And we don't need a huge refactoring for this.
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