为Hadoop创建JAR包文件Creating a JAR for Hadoop

We've seen the internals of MapReduce in the last post. Now we can make a little change to the WordCount and create a JAR for being executed by Hadoop. 
If we look at the result of the WordCount we ran before, the lines of the file are only split by space, and thus all other punctuation characters and symbols remain attached to the words and in some way "invalidate" the count. For example, we can see some of these wrong values:

KING 1
KING'S 1
KING. 5
King 6
King, 4
King. 2
King; 1

The word is always king but sometimes it appears in upper case, sometimes in lower case, or with a punctuation character after it. So we'd like to update the behaviour of the WordCount program to count all the occurrences of any word, aside from the punctuation and other symbols. In order to do so, we have to modify the code of the mapper, since it's here that we get the data from the file and split it. 
If we look at the code of mapper:

public static class TokenizerMapper extends Mapper<object, text,="" intwritable=""> {

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

      public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
          StringTokenizer itr = new StringTokenizer(value.toString());
          while (itr.hasMoreTokens()) {
              word.set(itr.nextToken());
              context.write(word, one);
          }
     }
}

we see that the StringTokenizer takes the line as the parameter; before doing that, we remove all the symbols from the line using a RegExp that maps each of these symbols into a space:

String cleanLine = value.toString().toLowerCase().replaceAll("[_|$#<>\\[\\]\\*/\\\\,;,.\\-:()?!\"']", " ");

that simply says "if you see any of these character _, |, $, #, <, >, [, ], *, /, \, ,, ;, ., -, :, ,(, ), ?, !, ", ' transform it into a space". All the backslashes are needed for correctly escaping the characters. Then we trim the token to avoid empty tokens:

itr.nextToken().trim()

So now the code looks like this (the updates to the original file are printed in bold):

public static class TokenizerMapper extends Mapper<object, text,="" intwritable=""> {

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

    @Override
    public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
        String cleanLine = value.toString().toLowerCase().replaceAll("[_|$#<>\\^=\\[\\]\\*/\\\\,;,.\\-:()?!\"']", " ");
        StringTokenizer itr = new StringTokenizer(cleanLine);
        while (itr.hasMoreTokens()) {
            word.set(itr.nextToken().trim());
            context.write(word, one);
        }
    }
}

The complete code of the class is available on my github repository.

We now want to create the JAR to be executed; to do it, we have to go to the output directory of our wordcount file (the directory that contains the .class files) and create a manifest filenamed manifest_file that contains something like this:

Manifest-Version: 1.0
Main-Class: samples.wordcount.WordCount

in which we tell the JAR which class to execute at startup. More details in Java official documentation. Note that there's no need to add classpath info, because the JAR will be run by Hadoop that already has a classpath that contains all needed libraries. 
Now we can launch the command:

$ jar cmf manifest_file wordcount.jar .

that creates a JAR named wordcount.jar that contains all classes starting from this directory (the . parameter) e using the content of manifest_file to create a Manifest. 
We can run the batch as we saw before. Looking at the result file we can check that there are no more symbols and punctuation characters; the occurrences of the word king is now the sum of all occurrences we found before:

king 20

which is what we were looking for.

from: http://andreaiacono.blogspot.com/2014/02/creating-jar-for-hadoop.html