example1.scala

import org.apache.spark.sql.functions

type myFunctionType = (Int, Long, String) => Int
val myFunction: myFunctionType = (i, l, str) => i + l.toInt + Integer.parseInt(str)
val myUDF = functions.udf(myFunction)

example2.scala

type myFunction2Type = (Long, java.lang.Double, String) => Tuple2[Double, String]
val myFunction2: myFunction2Type = (l, d, str) => (d + l, str)
val myUDF2 = functions.udf(myFunction2)

example3.scala

val colList = List[Column](
  originalDF("long_column"),
  originalDF("double_column"),
  originalDF("string_column")
)
val processedDF = originalDF
  .withColumn("newCol", myUDF2(colList:_*))
  .select("newCol._1", "newCol._2")