Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/18113#discussion_r118821260
--- 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 --
We can apply an aggregate on a dataset without groupBy. E.g.,
val ds = Seq.empty[(Int, Int)].toDS
ds.agg(typed.sum((x: (Int, Int))=> x._2)).show()
In this case, seems this typed `TypedMinDouble` will return the initial
value from the `zero` variable. I've not tried it, but looks like it will get
`Double.PositiveInfinity`. Beside the fact it's inconsistent with
`aggregate.Min`, getting positive infinity here can't be a correct result too.
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