org.apache.hadoop.mapreduce
Class Mapper<KEYIN,VALUEIN,KEYOUT,VALUEOUT>

java.lang.Object
  extended by org.apache.hadoop.mapreduce.Mapper<KEYIN,VALUEIN,KEYOUT,VALUEOUT>
Direct Known Subclasses:
ChainMapper, FieldSelectionMapper, InverseMapper, MultithreadedMapper, RegexMapper, TokenCounterMapper, ValueAggregatorMapper, WrappedMapper

@InterfaceAudience.Public
@InterfaceStability.Stable
public class Mapper<KEYIN,VALUEIN,KEYOUT,VALUEOUT>
extends Object

Maps input key/value pairs to a set of intermediate key/value pairs.

Maps are the individual tasks which transform input records into a intermediate records. The transformed intermediate records need not be of the same type as the input records. A given input pair may map to zero or many output pairs.

The Hadoop Map-Reduce framework spawns one map task for each InputSplit generated by the InputFormat for the job. Mapper implementations can access the Configuration for the job via the JobContext.getConfiguration().

The framework first calls setup(org.apache.hadoop.mapreduce.Mapper.Context), followed by map(Object, Object, Context) for each key/value pair in the InputSplit. Finally cleanup(Context) is called.

All intermediate values associated with a given output key are subsequently grouped by the framework, and passed to a Reducer to determine the final output. Users can control the sorting and grouping by specifying two key RawComparator classes.

The Mapper outputs are partitioned per Reducer. Users can control which keys (and hence records) go to which Reducer by implementing a custom Partitioner.

Users can optionally specify a combiner, via Job.setCombinerClass(Class), to perform local aggregation of the intermediate outputs, which helps to cut down the amount of data transferred from the Mapper to the Reducer.

Applications can specify if and how the intermediate outputs are to be compressed and which CompressionCodecs are to be used via the Configuration.

If the job has zero reduces then the output of the Mapper is directly written to the OutputFormat without sorting by keys.

Example:

 public class TokenCounterMapper 
     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);
     }
   }
 }
 

Applications may override the run(Context) method to exert greater control on map processing e.g. multi-threaded Mappers etc.

See Also:
InputFormat, JobContext, Partitioner, Reducer

Constructor Summary
Mapper()
           
 
Method Summary
protected  void cleanup(org.apache.hadoop.mapreduce.Mapper.Context context)
          Called once at the end of the task.
protected  void map(KEYIN key, VALUEIN value, org.apache.hadoop.mapreduce.Mapper.Context context)
          Called once for each key/value pair in the input split.
 void run(org.apache.hadoop.mapreduce.Mapper.Context context)
          Expert users can override this method for more complete control over the execution of the Mapper.
protected  void setup(org.apache.hadoop.mapreduce.Mapper.Context context)
          Called once at the beginning of the task.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

Mapper

public Mapper()
Method Detail

setup

protected void setup(org.apache.hadoop.mapreduce.Mapper.Context context)
              throws IOException,
                     InterruptedException
Called once at the beginning of the task.

Throws:
IOException
InterruptedException

map

protected void map(KEYIN key,
                   VALUEIN value,
                   org.apache.hadoop.mapreduce.Mapper.Context context)
            throws IOException,
                   InterruptedException
Called once for each key/value pair in the input split. Most applications should override this, but the default is the identity function.

Throws:
IOException
InterruptedException

cleanup

protected void cleanup(org.apache.hadoop.mapreduce.Mapper.Context context)
                throws IOException,
                       InterruptedException
Called once at the end of the task.

Throws:
IOException
InterruptedException

run

public void run(org.apache.hadoop.mapreduce.Mapper.Context context)
         throws IOException,
                InterruptedException
Expert users can override this method for more complete control over the execution of the Mapper.

Parameters:
context -
Throws:
IOException
InterruptedException


Copyright © 2012 Apache Software Foundation. All Rights Reserved.