Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/18113#discussion_r118932092
--- 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 --
A modified version of existing `TypedSumDouble` to use `java.lang.Double`
as `BUF` and `OUT` looks like below. It returns `null` when applying on an
empty dataset.
class TypedSumDouble[IN](val f: IN => Double)
extends Aggregator[IN, java.lang.Double, java.lang.Double] {
override def zero: java.lang.Double = null
override def reduce(b: java.lang.Double, a: IN): java.lang.Double = {
if (b == null) {
f(a)
} else {
b + f(a)
}
}
override def merge(b1: java.lang.Double, b2: java.lang.Double):
java.lang.Double = {
if (b1 == null) {
b2
} else if (b2 == null) {
b1
} else {
b1 + b2
}
}
override def finish(reduction: java.lang.Double): java.lang.Double = {
reduction
}
override def bufferEncoder: Encoder[java.lang.Double] =
ExpressionEncoder[java.lang.Double]()
override def outputEncoder: Encoder[java.lang.Double] =
ExpressionEncoder[java.lang.Double]()
// Java api support
def this(f: MapFunction[IN, java.lang.Double]) = this(x => f.call(x))
def toColumnJava: TypedColumn[IN, java.lang.Double] = {
toColumn.asInstanceOf[TypedColumn[IN, java.lang.Double]]
}
}
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