org.apache.hadoop.mapred.lib

Class TokenCountMapper<K>

java.lang.Object

org.apache.hadoop.mapred.MapReduceBase

org.apache.hadoop.mapred.lib.TokenCountMapper<K>

All Implemented Interfaces:

Closeable, AutoCloseable, JobConfigurable, Mapper<K,Text,Text,LongWritable>

@InterfaceAudience.Public
 @InterfaceStability.Stable
public class TokenCountMapper<K>
extends MapReduceBase
implements Mapper<K,Text,Text,LongWritable>

A Mapper that maps text values into <token,freq> pairs. Uses StringTokenizer to break text into tokens.

Constructor Summary

Constructors

Constructor and Description
TokenCountMapper()

Method Summary

Modifier and Type	Method and Description
void	map(K key, Text value, OutputCollector<Text,LongWritable> output, Reporter reporter) Maps a single input key/value pair into an intermediate key/value pair.

Methods inherited from class org.apache.hadoop.mapred.MapReduceBase

close, configure

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.hadoop.mapred.JobConfigurable

configure

Methods inherited from interface java.io.Closeable

close

Constructor Detail

TokenCountMapper

public TokenCountMapper()

Method Detail

map

public void map(K key,
                Text value,
                OutputCollector<Text,LongWritable> output,
                Reporter reporter)
         throws IOException

Description copied from interface: Mapper

Maps a single input key/value pair into an intermediate key/value pair.

Output pairs need not be of the same types as input pairs. A given input pair may map to zero or many output pairs. Output pairs are collected with calls to OutputCollector.collect(Object,Object).

Applications can use the Reporter provided to report progress or just indicate that they are alive. In scenarios where the application takes significant amount of time to process individual key/value pairs, this is crucial since the framework might assume that the task has timed-out and kill that task. The other way of avoiding this is to set mapreduce.task.timeout to a high-enough value (or even zero for no time-outs).

Specified by:

map in interface Mapper<K,Text,Text,LongWritable>

Parameters:

key - the input key.

value - the input value.

output - collects mapped keys and values.

reporter - facility to report progress.

Throws:

IOException