Hadoop入门（二十三）Mapreduce的求数量最大程序

一、简介

在文件中统计出现最多个数的单词，将其输出到hdfs文件上。

 

二、例子

（1）实例描述
给出三个文件，每个文件中都若干个单词以空白符分隔，需要统计出现最多的单词                                            

样例输入：                                            
1）file1：  

MapReduce is simple

2）file2：  

MapReduce is powerful is simple 

3）file3：  

Hello MapReduce bye MapReduce

期望输出：

MapReduce      4

（2）问题分析
实现"统计出现最多个数的单词"只要关注的信息为：单词、词频。

 

（3）实现步骤

1）Map过程 

首先使用默认的TextInputFormat类对输入文件进行处理，得到文本中每行的偏移量及其内容。显然，Map过程首先必须分析输入的<key,value>对，得到倒排索引中需要的三个信息：单词、词频

2）Combine过程 
    经过map方法处理后，Combine过程将key值相同的value值累加，得到一个单词在文档在文档中的词频，输出作为Reduce过程的输入。

3）Reduce过程 
经过上述两个过程后，Reduce过程只需将相同key值的value值累加，保留最大词频的单词输出。

 

（4）代码实现

package com.mk.mapreduce;


import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.FileSplit;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.IOException;
import java.net.URI;
import java.util.*;

public class MaxWord {

    public static class MaxWordMapper extends Mapper<LongWritable, Text, Text, IntWritable> {

        private final Text newKey = new Text();
        private final IntWritable newValue = new IntWritable(1);

        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

            if (StringUtils.isBlank(value.toString())) {
                System.out.println("空白行");
                return;
            }
            StringTokenizer tokenizer = new StringTokenizer(value.toString());
            while (tokenizer.hasMoreTokens()) {
                String word = tokenizer.nextToken();
                newKey.set(word);
                context.write(newKey, newValue);
            }
        }
    }

    public static class MaxWordCombiner extends Reducer<Text, IntWritable, Text, IntWritable> {

        private final IntWritable newValue = new IntWritable();

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


            int count = 0;
            for (IntWritable v : values) {
                count += v.get();
            }
            newValue.set(count);
            context.write(key, newValue);

        }
    }

    public static class MaxWordReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

        private String word = null;
        private int count = 0;

        @Override
        protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int c = 0;
            for (IntWritable v : values) {
                c += v.get();
            }
            if (word == null || count < c) {
                word = key.toString();
                count = c;
            }

        }

        @Override
        protected void cleanup(Context context) throws IOException, InterruptedException {
            if (word != null) {
                context.write(new Text(word), new IntWritable(count));
            }

        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {

        String uri = "hdfs://192.168.150.128:9000";
        String input = "/maxWord/input";
        String output = "/maxWord/output";
        Configuration conf = new Configuration();
        if (System.getProperty("os.name").toLowerCase().contains("win"))
            conf.set("mapreduce.app-submission.cross-platform", "true");

        FileSystem fileSystem = FileSystem.get(URI.create(uri), conf);
        Path path = new Path(output);
        fileSystem.delete(path, true);

        Job job = new Job(conf, "MaxWord");
        job.setJar("./out/artifacts/hadoop_test_jar/hadoop-test.jar");
        job.setJarByClass(MaxWord.class);
        job.setMapperClass(MaxWordMapper.class);
        job.setCombinerClass(MaxWordCombiner.class);
        job.setReducerClass(MaxWordReducer.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPaths(job, uri + input);
        FileOutputFormat.setOutputPath(job, new Path(uri + output));


        boolean ret = job.waitForCompletion(true);
        System.out.println(job.getJobName() + "-----" + ret);
    }
}