org.apache.hadoop.mapred.lib
Class LongSumReducer<K>

java.lang.Object
  org.apache.hadoop.mapred.MapReduceBase
      org.apache.hadoop.mapred.lib.LongSumReducer<K>

All Implemented Interfaces:

Closeable, JobConfigurable, Reducer<K,LongWritable,K,LongWritable>

@InterfaceAudience.Public
@InterfaceStability.Stable
public class LongSumReducer<K>
extends MapReduceBase
implements Reducer<K,LongWritable,K,LongWritable>

A Reducer that sums long values.

Constructor Summary

LongSumReducer()

Method Summary

void	reduce(K key, Iterator<LongWritable> values, OutputCollector<K,LongWritable> output, Reporter reporter) Reduces values for a given key.

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

LongSumReducer

public LongSumReducer()

Method Detail

reduce

public void reduce(K key,
                   Iterator<LongWritable> values,
                   OutputCollector<K,LongWritable> output,
                   Reporter reporter)
            throws IOException

Description copied from interface: Reducer

Reduces values for a given key.

The framework calls this method for each <key, (list of values)> pair in the grouped inputs. Output values must be of the same type as input values. Input keys must not be altered. The framework will reuse the key and value objects that are passed into the reduce, therefore the application should clone the objects they want to keep a copy of. In many cases, all values are combined into zero or one value.

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 a 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:

reduce in interface Reducer<K,LongWritable,K,LongWritable>

Parameters:

key - the key.

values - the list of values to reduce.

output - to collect keys and combined values.

reporter - facility to report progress.

Throws:

IOException