Spark DataFrame: Computing row-wise mean (or any aggregate operation)

Question

I have a Spark DataFrame loaded up in memory, and I want to take the mean (or any aggregate operation) over the columns. How would I do that? (In numpy, this is

Answer 1

in Scala something like this would do it

val cols = Seq("US","UK","Can")
f.map(r => (r.getAs[Int]("id"),r.getValuesMap(cols).values.fold(0.0)(_+_)/cols.length)).toDF