java.lang.NoClassDefFoundError: Could not initialize class mainPrincipal $ in Apace Spark

Hi, first of all, thank you.

I present problems when executing the following code in a cluster with Spark, if I execute it as master ("local [*]") it does not give problems everything perfect, but once I execute it in the following way

  

/home/cluster/opt/spark-2.2.1-bin-hadoop2.7/bin/spark-submit --master spark: //10.8.176.90: 7077 --class mainPrincipate JARname.jar filename.csv

presents the following error

  

Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: ..... java.lang.NoClassDefFoundError: Could not initialize class mainPrincipal $

     

at mainPrincipal $$ anonfun $ 2.apply (mainPrincipal.scala.25) which is the line that says "val tuplas = datos.map {row = > parseTupla (row)}"

this is my code:

object mainPrincipal {

  val spark: SparkSession = SparkSession
                            .builder()
                            .appName("Nombre de la Aplicación")
                            .getOrCreate()  

  def main(args: Array[String]): Unit = {

    val nombreDelfichero = args(0)

    import spark.implicits._

    val datos = spark.read.format("csv").option("header", "false").csv(nombreDelfichero)

    val tuplas = datos.map{row => parseTupla(row)} //RDD de Tupla(id: Long, valores: Seq[Double])
    tuplas.persist(StorageLevel.MEMORY_AND_DISK_SER)

    tuplas.foreach( element1 =>{
      println("Id "+element1._1.toString) 
    }
  } 

  case class Tupla(id: Long, valores: Seq[Double]) extends Serializable

  def parseTupla(row: Row): Tupla ={
    var coordenadas : Seq[Double] = Seq.empty[Double]

    val cant = row.size
    val id = row.getString(cant-1).toLong
    for(i <- 0 until cant-1)
    {
      coordenadas = coordenadas :+ row.getString(i).toDouble
    }

    Tupla( id,coordenadas)
  }
}

I have consulted subjects but they are similar and I still do not have a solution, I would appreciate cooperation, as soon as possible and I would like to thank you again.