Hi everyone,
I was able to solve this issue. For now I changed the library code and added the following to the class com.wcohen.ss.BasicStringWrapper: 

public class BasicStringWrapper implements  Serializable

However, I am still curious to know ho to get around the issue when you don't have access to the code and you are using a 3rd party jar.



From: sstilak@live.com
To: user@spark.incubator.apache.org
Subject: Serialization of objects
Date: Thu, 26 Jun 2014 09:30:31 -0700

Hi everyone,

Aaron, thanks for your help so far. I am trying to serialize objects that I instantiate from a 3rd party library namely instances of com.wcohen.ss.Jaccard, and com.wcohen.ss.BasicStringWrapper. However, I am having problems with serialization. I am (at least trying to) using Kryo for serialization. I  am still facing the serialization issue. I get "org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: com.wcohen.ss.BasicStringWrapper" Any help with this will be great.  
Scala code:

package approxstrmatch

import com.wcohen.ss.BasicStringWrapper;
import com.wcohen.ss.Jaccard;

import java.util.Iterator;

import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf

import org.apache.spark.rdd;
import org.apache.spark.rdd.RDD;

import com.esotericsoftware.kryo.Kryo
import org.apache.spark.serializer.KryoRegistrator

class MyRegistrator extends KryoRegistrator {
  override def registerClasses(kryo: Kryo) {
    kryo.register(classOf[approxstrmatch.JaccardScore])
    kryo.register(classOf[com.wcohen.ss.BasicStringWrapper])
    kryo.register(classOf[com.wcohen.ss.Jaccard])

  }
}

class JaccardScore  {

  val mjc = new Jaccard()  with Serializable
  val conf = new SparkConf().setMaster("spark://pzxnvm2018:7077").setAppName("ApproxStrMatch")
  conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
  conf.set("spark.kryo.registrator", "approxstrmatch.MyRegistrator")

  val sc = new SparkContext(conf)

  def calculateScoreSecond (sourcerdd: RDD[String], destrdd: RDD[String])  {
  val jc_ = this.mjc

  var i: Int = 0
  for (sentence <- sourcerdd.toLocalIterator)
   {    val str1 = new BasicStringWrapper (sentence)
        var scorevector = destrdd.map(x => jc_.score(str1, new BasicStringWrapper(x)))
        val fileName = new String("/apps/software/scala-approsstrmatch-sentence" + i)
        scorevector.saveAsTextFile(fileName)
        i += 1
   }

  }

Here is the script:
 val distFile = sc.textFile("hdfs://serverip:54310/data/dummy/sample.txt");
 val srcFile = sc.textFile("hdfs://serverip:54310/data/dummy/test.txt");
 val score = new approxstrmatch.JaccardScore()
 score.calculateScoreSecond(srcFile, distFile) 

O/P:

14/06/25 12:32:05 INFO DAGScheduler: Submitting Stage 0 (MappedRDD[3] at textFile at <console>:12), which has no missing parents
14/06/25 12:32:05 INFO DAGScheduler: Submitting 1 missing tasks from Stage 0 (MappedRDD[3] at textFile at <console>:12)
14/06/25 12:32:05 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
14/06/25 12:32:05 INFO TaskSetManager: Starting task 0.0:0 as TID 0 on executor localhost: localhost (PROCESS_LOCAL)
14/06/25 12:32:05 INFO TaskSetManager: Serialized task 0.0:0 as 1879 bytes in 4 ms
14/06/25 12:32:05 INFO Executor: Running task ID 0
14/06/25 12:32:05 INFO Executor: Fetching http://serverip:47417/jars/approxstrmatch.jar with timestamp 1403724701564
14/06/25 12:32:05 INFO Utils: Fetching http://serverip:47417/jars/approxstrmatch.jar to /tmp/fetchFileTemp8194323811657370518.tmp
14/06/25 12:32:05 INFO Executor: Adding file:/tmp/spark-397828b5-3e0e-4bb4-b56b-58895eb4d6df/approxstrmatch.jar to class loader
14/06/25 12:32:05 INFO Executor: Fetching http://serverip:47417/jars/secondstring-20140618.jar with timestamp 1403724701562
14/06/25 12:32:05 INFO Utils: Fetching http://serverip:47417/jars/secondstring-20140618.jar to /tmp/fetchFileTemp8711755318201511766.tmp
14/06/25 12:32:06 INFO Executor: Adding file:/tmp/spark-397828b5-3e0e-4bb4-b56b-58895eb4d6df/secondstring-20140618.jar to class loader
14/06/25 12:32:06 INFO BlockManager: Found block broadcast_1 locally
14/06/25 12:32:06 INFO HadoopRDD: Input split: hdfs://serverip:54310/data/dummy/test.txt:0+140
14/06/25 12:32:06 INFO Executor: Serialized size of result for 0 is 717
14/06/25 12:32:06 INFO Executor: Sending result for 0 directly to driver
14/06/25 12:32:06 INFO Executor: Finished task ID 0
14/06/25 12:32:06 INFO TaskSetManager: Finished TID 0 in 227 ms on localhost (progress: 1/1)
14/06/25 12:32:06 INFO DAGScheduler: Completed ResultTask(0, 0)
14/06/25 12:32:06 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
14/06/25 12:32:06 INFO DAGScheduler: Stage 0 (apply at Iterator.scala:371) finished in 0.242 s
14/06/25 12:32:06 INFO SparkContext: Job finished: apply at Iterator.scala:371, took 0.34204941 s
14/06/25 12:32:06 INFO FileInputFormat: Total input paths to process : 1
14/06/25 12:32:06 INFO SparkContext: Starting job: saveAsTextFile at JaccardScore.scala:52
14/06/25 12:32:06 INFO DAGScheduler: Got job 1 (saveAsTextFile at JaccardScore.scala:52) with 2 output partitions (allowLocal=false)
14/06/25 12:32:06 INFO DAGScheduler: Final stage: Stage 1(saveAsTextFile at JaccardScore.scala:52)
14/06/25 12:32:06 INFO DAGScheduler: Parents of final stage: List()
14/06/25 12:32:06 INFO DAGScheduler: Missing parents: List()
14/06/25 12:32:06 INFO DAGScheduler: Submitting Stage 1 (MappedRDD[5] at saveAsTextFile at JaccardScore.scala:52), which has no missing parents
14/06/25 12:32:06 INFO DAGScheduler: Failed to run saveAsTextFile at JaccardScore.scala:52
org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: com.wcohen.ss.BasicStringWrapper
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:770)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:713)
at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1176)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)