CODEWITHSUNDEEP
scalaapache-sparkrdd
Laure D
Laure D

Reputation: 887

Create a RDD : too many fields => use case class for RDD

I have a dataset of intrusion which is labeled that I want to use to test different supervised machine learning techniques.

So here is a part of my code :

object parser_dataset {

   val conf = new SparkConf()
       .setMaster("local[2]")
       .setAppName("kdd")
       .set("spark.executor.memory", "8g")
        conf.registerKryoClasses(Array(
        classOf[Array[Any]],
        classOf[Array[scala.Tuple3[Int, Int, Int]]],
        classOf[String],
        classOf[Any]
    ))
    val context = new SparkContext(conf)

    def load(file: String): RDD[(Int, String, String,String,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Int,Double,Double,Double,Double,Double,Double,Double, Int, Int,Double, Double, Double, Double, Double, Double, Double, Double, String)] = {

        val data = context.textFile(file)

        val res = data.map(x => {

            val s = x.split(",")
        (s(0).toInt, s(1), s(2), s(3), s(4).toInt, s(5).toInt, s(6).toInt, s(7).toInt, s(8).toInt, s(9).toInt, s(10).toInt, s(11).toInt, s(12).toInt, s(13).toInt, s(14).toInt, s(15).toInt, s(16).toInt, s(17).toInt, s(18).toInt, s(19).toInt, s(20).toInt, s(21).toInt, s(22).toInt, s(23).toInt, s(24).toDouble, s(25).toDouble, s(26).toDouble, s(27).toDouble, s(28).toDouble, s(29).toDouble, s(30).toDouble, s(31).toInt, s(32).toInt, s(33).toDouble, s(34).toDouble, s(35).toDouble, s(36).toDouble, s(37).toDouble, s(38).toDouble, s(39).toDouble, s(40).toDouble, s(41))    
        })
        .persist(StorageLevel.MEMORY_AND_DISK)
    return res
    }


   def main(args: Array[String]) {
     val data = this.load("/home/hvfd8529/Datasets/KDDCup99/kddcup.data_10_percent_corrected")

     data1.collect.foreach(println)
     data.distinct() 

    }

}

This is not my code, it was given to me and I just modified some parts (especially the RDD and splitting parts) and I'm a newbie at Scala and Spark :)

EDIT: So I added case class above my load function, like this :

case class BasicFeatures(duration:Int, protocol_type:String, service:String, flag:String, src_bytes:Int, dst_bytes:Int, land:Int, wrong_fragment:Int, urgent:Int) 

case class ContentFeatures(hot:Int, num_failed_logins:Int, logged_in:Int, num_compromised:Int, root_shell:Int, su_attempted:Int, num_root:Int, num_file_creations:Int, num_shells:Int, num_access_files:Int, num_outbound_cmds:Int, is_host_login:Int, is_guest_login:Int)

case class TrafficFeatures(count:Int, srv_count:Int, serror_rate:Double, srv_error_rate:Double, rerror_rate:Double, srv_rerror_rate:Double, same_srv_rate:Double, diff_srv_rate:Double, srv_diff_host_rate:Double, dst_host_count:Int, dst_host_srv_count:Int, dst_host_same_srv_rate:Double, dst_host_diff_srv_rate:Double, dst_host_same_src_port_rate:Double, dst_host_srv_diff_host_rate:Double, dst_host_serror_rate:Double, dst_host_srv_serror_rate:Double, dst_host_rerror_rate:Double, dst_host_srv_rerror_rate:Double, attack_type:String )

But now I am confused, how can I use these to solve my problem, because I still need a RDD in order to have one feature = one field Here is my one line of my file I want to parse :

0,tcp,ftp_data,SF,491,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,2,0.00,0.00,0.00,0.00,1.00,0.00,0.00,150,25,0.17,0.03,0.17,0.00,0.00,0.00,0.05,0.00,normal,20

Upvotes: 0

Views: 486

Answers (1)

Ashish Singh
Ashish Singh

Reputation: 533

Max tuple size supported by Scala is 22.Scala function have limit of 22 Parameter. Hence you can not create tuple of size more that 22.

Upvotes: 0

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