Github user setjet commented on a diff in the pull request:
https://github.com/apache/spark/pull/18113#discussion_r118822478
--- 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 --
Hmm it seems that typedAvg (already implemented), returns a NaN, while
aggregate.Min returns null.
Aligning it with typedAvg would not be possible for minLong, as NaN is only
availble for Double of course. Another possibility of course would be to wrap
it in Option type, but that again is not completely in line with aggregate.Min.
This is because aggregate.Min is expression based, which has built in support
for null as it extends aggregate.interfaces.DeclarativeAggregate, whereas
typedaggregators extend Aggregator.
Aligning this properly seems like a huge refactor. What do you think the
best approach is?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
