calculating kurtosis array[Double] filed in spark scala

Question

how to calculate the kurtosis of array field in spark

spark built-in function is failing array field.

due to data type mismatch: argument 1 requires double type, however, 'SERIES' is of array<double> type.;;

Example in python

 from scipy.stats import kurtosis
 kurtosis([1, 2, 3, 4, 5])
-1.3

i used spark built in function

df.withColumn("newcolumn",when(col("SERIES").isNotNull,kurtosis(columnName))

Answer 1

using Twitter Algebra package i can get kurtosis value.

import com.twitter.algebird._
val y  = List(1, 2, 3, 4, 5)
def getMoments(xs: List[Int]): Moments =
xs.foldLeft(MomentsGroup.zero) { (m, x) =>
  MomentsGroup.plus(m, Moments(x))
}

println(getMoments(y).kurtosis) // -1.3