Eccezione non serializzabile durante l'esecuzione del processo spark di apache

Question

Il seguente programma java è stato scritto per sperimentare la scintilla di apache.

Il programma tenta di leggere un elenco di parole positive e negative da un file rispettivo, confrontarlo con il file master e filtrare i risultati di conseguenza.

import java.io.Serializable; 
import java.io.FileNotFoundException; 
import java.io.File; 
import java.util.*; 
import java.util.Iterator; 
import java.util.List; 
import java.util.List; 
import org.apache.spark.api.java.*; 
import org.apache.spark.api.java.function.Function; 

public class SimpleApp implements Serializable{ 
    public static void main(String[] args) { 
    String logFile = "/tmp/master.txt"; // Should be some file on your system 
    String positive = "/tmp/positive.txt"; // Should be some file on your system 
    String negative = "/tmp/negative.txt"; // Should be some file on your system 

    JavaSparkContext sc = new JavaSparkContext("local[4]", "Twitter Analyzer", "/home/welcome/Downloads/spark-1.1.0/", new String[]{"target/scala-2.10/Simple-assembly-0.1.0.jar"}); 

    JavaRDD<String> positiveComments = sc.textFile(logFile).cache(); 

    List<String> positiveList = GetSentiments(positive); 
    List<String> negativeList= GetSentiments(negative); 

    final Iterator<String> iterator = positiveList.iterator(); 
    int i = 0; 
    while (iterator.hasNext()) 
    { 
     JavaRDD<String> numAs = positiveComments.filter(new Function<String, Boolean>() 
     { 
     public Boolean call(String s) 
     { 
      return s.contains(iterator.next()); 
     } 
     }); 

    numAs.saveAsTextFile("/tmp/output/"+ i); 
    i++; 
    } 

    } 

public static List<String> GetSentiments(String fileName) { 
    List<String> input = new ArrayList<String>(); 
try 
{ 
    Scanner sc = new Scanner(new File(fileName)); 

    while (sc.hasNextLine()) { 
     input.add(sc.nextLine()); 
    } 
} 
catch (FileNotFoundException e){ 
    // do stuff here.. 
} 
    return input; 
} 

} 

L'errore seguente è gettata durante l'esecuzione del lavoro scintilla,

Exception in thread "main" org.apache.spark.SparkException: Task not serializable 
    at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) 
    at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) 
    at org.apache.spark.SparkContext.clean(SparkContext.scala:1242) 
    at org.apache.spark.rdd.RDD.filter(RDD.scala:282) 
    at org.apache.spark.api.java.JavaRDD.filter(JavaRDD.scala:78) 
    at SimpleApp.main(SimpleApp.java:37) 
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) 
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 
    at java.lang.reflect.Method.invoke(Method.java:606) 
    at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:328) 
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75) 
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 
Caused by: java.io.NotSerializableException: java.util.ArrayList$Itr 
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1183) 
    at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) 
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) 
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) 
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177) 
    at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) 
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) 
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) 
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177) 
    at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347) 
    at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:42) 
    at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:73) 
    at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:164) 
    ... 12 more 

Qualsiasi puntatori ??

Answer 1

Quando si crea una classe anonima, il compilatore fa alcune cose:

JavaRDD<String> numAs = positiveComments.filter(new Function<String, Boolean>() 
     { 
     public Boolean call(String s) 
     { 
      return s.contains(iterator.next()); 
     } 
     }); 

Sarà riscritto come:

JavaRDD<String> numAs = positiveComments.filter(new Function<String, Boolean>() 
     { 
     private Iterator<...> $iterator; 
     public Boolean call(String s) 
     { 
      return s.contains($iterator.next()); 
     } 
     }); 

Questo è il motivo per cui si può avere un NotSerializableException perché l'Iterator non è serializzabile.

Per evitare che, semplicemente estrarre il risultato della successiva prima:

String value = iterator.next(); 
JavaRDD<String> numAs = positiveComments.filter(new Function<String, Boolean>() 
     { 
     public Boolean call(String s) 
     { 
      return s.contains(value); 
     } 
     }); 

Answer 2

Alcuni Java I fatti

1. Any anonymous class defined inside a outer class has reference to the outer class. 
    2. If the anonymous class needs to be serialized it will compel you to make the outer class serialized. 
    3. Inside the lambda function if one uses a method of the enclosing class , the class needs to be serialized , if the lambda function is being serialized. 

alcuni fatti su Spark.

1. On Same Executor multiple tasks can run at the same time in the same JVM as Tasks are spawned as threads in spark. 
2. Any lambda, Anonymous Class used with the spark Transformation function (map, mapPartitions, keyBy , redudeByKey …) will be instantiated on driver, serialized and sent to the executor. 
3. To serialize an object means to convert its state to a byte stream so that the byte stream can be reverted back into a copy of the object. 
4. A Java object is serializable if its class or any of its super class implements either the java.io.Serializable interface or its subinterface, java.io.Externalizable. 

Regola generale per evitare problemi di serializzazione:

1. Avoid using anonymous class , instead use static classes as anonymous class will force you to have the outer class serialized. 
    2. Avoid using static variables as a work around for serialization issue , as Multiple Task can run inside the same JVM and the static instance might not be thread safe. 
    3. Use Transient variables to avoid serialization issue , you will have to initialize them inside the function call and not Constructor. As on driver the constructor will be called , on Executor it will de-serialize and for the object . only way to initialize is inside the function call . 
    4. Use Static class in place of anonymous class. 
    5. Religiously follow ” attaching implements Serializable ” only for the classes which only needs to be serialized 
    6. Inside a “lambda function” never refer to outclass method directly , as this will lead to serialization of outer class. 
    7. Make methods static if it needs to be used within Lambda function directly , else use Class::func() notion but not func() directly 
    8. Java Map<> doesn’t implement Serializable but HashMap does . 
    9. Be wise when deciding over using Braodcast vs Raw DataStructures. If you see a real benefit then only use Broadcast. 

Per una comprensione approfondita in seguito http://bytepadding.com/big-data/spark/understanding-spark-serialization/