zeppelin load file, input parameters and transform text

zep1

//** Should be a maven or gradle project and use 0.62 https://zeppelin.apache.org/download.html and scala 2.11, spark spark-2.0.1-bin-hadoop2.7
//** Your example should take 6 parameters so that can test 4 transformations including date. this example does not have date parsing.
//**  parse a date using DateFormat and use that date to compare to a column (is equal) from file 

import scala.util.matching.Regex
import org.apache.spark.sql.functions.udf
import org.apache.spark.sql.catalog.Column


def doRegReplace(orig: String, reg: Regex, rplc: String): String =
    {
      reg.replaceAllIn(orig, rplc)
    }


println("--- 1"  )
val pathOnServer = "/Users/u1/data2.csv"
val inColData = spark.read.option("header", "true").format("csv").option("inferSchema", "true").option("nullValue", null).load(pathOnServer).cache()
val val1 = z.input("val1", "2").toString().toInt
val val2 = z.input("val2", "Other info").toString()
val str1  = z.input("str1", "A|B|E|a|o").toString()
val str2  = z.input("str2", "X").toString()
val sdf = new java.text.SimpleDateFormat("yyyy-mm-dd")
val date1s = z.input("date1", "2016-12-04").toString()
val date1 = sdf.parse(date1s)
println("--- 2 date:" + date1 + "."  )
var outColData = inColData.withColumn("a2", inColData("a1") * val1)
val newCol = "c3"
val onCol = "c1"
val idx = 1
val re = str1.r
val rpl = str2
println("new c :" + newCol + ", on col :" + onCol + "." + ", value :" + re)
//re.replaceAllIn(inColData(onCol).toString()
val doRegReplace_udf = udf(doRegReplace(_: String, re, rpl))
outColData = outColData.withColumn(
newCol, doRegReplace_udf(inColData(onCol)))

println("---data7---" + idx  + val2)
outColData.collect().foreach(println)