Wordcount -- MapReduce example -- Mapper

Mapper maps input key/value pairs into intermediate key/value pairs.

E.g.

Input: (docID, doc)

Output: (term, 1)

Mapper Class Prototype:

Mapper<Object, Text, Text, IntWritable>
// Object:: INPUT_KEY
// Text:: INPUT_VALUE
// Text:: OUTPUT_KEY
// IntWritable:: OUTPUT_VALUE

Special Data Type for Mapper

IntWritable

A serializable and comparable object for integer.

Example:

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

Text

A serializable, deserializable and comparable object for string at byte level. It stores text in UTF-8 encoding.

Example:

private Text word = new Text();

Hadoop defines its own classes for general data types.

-- All "values" must have Writable interface;

-- All "keys" must have WritableComparable interface;

Map Method for Mapper

Method header

public void map(Object key, Text value, Context context
               ) throws IOException, InterruptedException
// Object key:: Declare data type of input key;
// Text value:: Declare data type of input value;
// Context context:: Declare data type of output. Context is often used for output data collection.

Tokenization

// Use Java built-in StringTokenizer to split input value (document) into words:
StringTokenizer itr = new StringTokenizer(value.toString());

Building (key, value) pairs

// Loop over all words:
while (itr.hasMoreTokens()) {
  // convert built-in String back to Text:
  word.set(itr.nextToken());
  // build (key, value) pairs into Context and emit:
  context.write(word, one);
}

Map Method Summary

Mapper class produces Mapper.Context object, which comprise a series of (key, value) pairs

  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);
    }
  }

Overview of Mapper Class

public static class TokenizerMapper
     extends Mapper<Object, Text, 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);
    }
  }
}