word.set（）メソッドはmap内にnullポインタ例外をスローしますreduce hadoop

Question

私はプログラミングを減らすために新しく、簡単な単語カウントの例でレッスンを始めました。しかし、私はそれとは異なるアプローチを試みています。私は自分のhdfs入力フォルダに2つの入力ファイルを持っています。私はキーで一緒に単語とファイル名を連結するためにマッパークラスを書いたが、私は、テキスト中のキー値を設定すると、それがnullポインタ例外をスローします。

anyword1 --> filename1  2 
anyword2 --> filename2  3 

ように、私は、出力を生成しようとしています誰かが助けて、私が間違っているところに助言することができますか？

マイマッパークラス

public static class TokenizerMapper 
     extends Mapper<Object, Text, Text,IntWritable>{ 

    private final static IntWritable one = new IntWritable(1); 
    private Text word = null; 
    private String fileText = null; 

    public void map(Object key, Text value, Context context 
        ) throws IOException, InterruptedException { 
     StringTokenizer itr = new StringTokenizer(value.toString()); 
     String fileName = ((FileSplit) context.getInputSplit()).getPath().getName(); 
     String modifiedWord =""; 
     fileName = "-->"+fileName; 
     System.out.println("filename before word-->"+fileName); 
     while (itr.hasMoreTokens()) { 
     modifiedWord = itr.nextToken().toString();//+fileName; 
     modifiedWord = modifiedWord + fileName; 
     System.out.println("modified word-->"+modifiedWord); 
     word.set(modifiedWord); 
     context.write(word, one); 
     System.out.println("Mapper context-->"+word); 
     } 
    } 
    } 

------ Exeption ----

[root@LinuxCentos7 hadoop]# hadoop jar /usr/local/mapreduceexample/WordCountEx3.jar /user/Siddharth/Input /user/Siddharth/output 
17/06/09 23:32:29 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032 
17/06/09 23:32:32 INFO input.FileInputFormat: Total input paths to process : 2 
17/06/09 23:32:32 INFO mapreduce.JobSubmitter: number of splits:2 
17/06/09 23:32:32 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1497025644387_0011 
17/06/09 23:32:33 INFO impl.YarnClientImpl: Submitted application application_1497025644387_0011 
17/06/09 23:32:33 INFO mapreduce.Job: The url to track the job: http://LinuxCentos7:8088/proxy/application_1497025644387_0011/ 
17/06/09 23:32:33 INFO mapreduce.Job: Running job: job_1497025644387_0011 
17/06/09 23:32:52 INFO mapreduce.Job: Job job_1497025644387_0011 running in uber mode : false 
17/06/09 23:32:52 INFO mapreduce.Job: map 0% reduce 0% 
17/06/09 23:33:16 INFO mapreduce.Job: map 100% reduce 0% 
17/06/09 23:33:16 INFO mapreduce.Job: Task Id : attempt_1497025644387_0011_m_000000_0, Status : FAILED 
Error: java.lang.NullPointerException 
    at com.hadoop.WordCountEx3$TokenizerMapper.map(WordCountEx3.java:56) 
    at com.hadoop.WordCountEx3$TokenizerMapper.map(WordCountEx3.java:1) 
    at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:146) 
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:787) 
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341) 
    at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164) 
    at java.security.AccessController.doPrivileged(Native Method) 
    at javax.security.auth.Subject.doAs(Subject.java:422) 
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698) 
    at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158) 

Answer 1

はTextインスタンスにword変数を初期化します。

private final static IntWritable one = new IntWritable(1); 
private Text word = new Text(); 
private String fileText = null; 

public void map(Object key, Text value, Context context) 
     throws IOException, InterruptedException { 
    ... 
}