Implementation:Heibaiying BigData Notes WordCountReducer Reduce

Knowledge Sources	BigData-Notes Hadoop API
Domains	Distributed_Computing, Big_Data
Last Updated	2026-02-10 10:00 GMT

Overview

Concrete tool for aggregating word occurrence counts into total frequencies provided by the BigData-Notes repository.

Description

The WordCountReducer class extends Hadoop's Reducer<Text, IntWritable, Text, IntWritable> and implements the reduce phase of the word count pipeline. For each unique word (key), the reduce() method iterates over all associated count values and computes their sum. It then emits a single (word, totalCount) pair representing the total number of occurrences of that word across the entire input dataset.

Because the summation operation is both associative and commutative, this reducer can also be reused as a Combiner for local pre-aggregation on the mapper side.

Usage

Use this reducer as part of a word count MapReduce job. It is registered with the job via job.setReducerClass(WordCountReducer.class) during job assembly. It can also be set as the Combiner via job.setCombinerClass(WordCountReducer.class).

Code Reference

Source Location

Repository: BigData-Notes
File: code/Hadoop/hadoop-word-count/src/main/java/com/heibaiying/component/WordCountReducer.java
Lines: L12-22

Signature

public class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context)
        throws IOException, InterruptedException
}

Import

import com.heibaiying.component.WordCountReducer;

I/O Contract

Inputs

Name	Type	Required	Description
key	Text	Yes	A unique word from the intermediate map output
values	Iterable<IntWritable>	Yes	An iterable of integer counts (each typically 1, or pre-aggregated by a Combiner)
context	Context	Yes	The Reducer context used to emit the final output key-value pair

Outputs

Name	Type	Description
key	Text	The word being counted
value	IntWritable	The total number of occurrences of the word across all input data

Usage Examples

Basic Usage

import com.heibaiying.component.WordCountReducer;
import org.apache.hadoop.mapreduce.Job;

// Register the reducer with a MapReduce job
Job job = Job.getInstance(conf, "WordCount");
job.setReducerClass(WordCountReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);

Internal Logic

// For key "Hadoop" with values [1, 1, 1, 1, 1]:
// The reduce method computes:
//   sum = 0
//   sum += 1  -> sum = 1
//   sum += 1  -> sum = 2
//   sum += 1  -> sum = 3
//   sum += 1  -> sum = 4
//   sum += 1  -> sum = 5
// Emits: ("Hadoop", 5)

Related Pages

Implements Principle

Principle:Heibaiying_BigData_Notes_MapReduce_Reduce_Phase

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