spark_udf_overload.scala

case class Person (name: String, age: Int)

val df = sc.parallelize(List(Person("Guilherme", 35), Person("Isabela", 6), Person("Daniel", 3))).toDF


def wordsLengthScala(a: Any): Array[Int] = {
  a match {
     case s: String => {s.split(" ").map(s => s.length)}
     case i: Integer => {Array(i)}
  } 
}

val wordsLengthScalaUDF = udf(wordsLengthScala _)

df.printSchema

df.show
df.select(wordsLengthScalaUDF(col("name")),wordsLengthScalaUDF(col("age"))).show