MapReduce之词频统计本地运行

1、上述的MapReduce之Mapper、Reducer、Driver三步实现，是基于输入和输出都是HDFS的

（1）输入：HADOOP_USER_NAME、
（2）输出：hdfs://192.168.126.101:8020

//WordCountApp.java       
        //设置权限
        System.setProperty("HADOOP_USER_NAME", "hadoop");

        Configuration configuration = new Configuration();
        //在configuration里设置一些东西：
        configuration.set("fs.defaultFS", "hdfs://192.168.126.101:8020");
        

 

2、不连HDFS，只在本地处理词频统计

（0）优势：运行速度快

（1）在hadoop-train-v2下新建Directory：input

（2）在input里新建file.text：WordCount.Input

（3）将h.txt内容考入WordCount.Input中

（4）在com.imooc.bigdata.hadoop.mapreduce.wordcount下复制WordCountApp.java为：WordCountLocalApp.java

 

3、WordCountLocalApp.java

package com.imooc.bigdata.hadoop.mapreduce.wordcount;


import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/*
 * Driver类：配置Mapper和Reducer的相关属性
 * 通过WordCountApp.java将Mapper和Reducer关联起来
 * 使用MapReduce统计HDFS上的文件对应的词频
 *
 * 使用本地文件进行统计，然后统计结果输出到本地路径
 */

public class WordCountLocalApp {

    public static void main(String[] args) throws Exception{

        Configuration configuration = new Configuration();

        //创建一个Job
        //将configuration传进来
        Job job = Job.getInstance(configuration);

        //设置Job对应的参数：主类
        job.setJarByClass(WordCountLocalApp.class);

        //设置Job对应的参数：设置自定义的Mapper和Reducer处理类
        job.setMapperClass(WordCountMapper.class);
        job.setReducerClass(WordCountReducer.class);

        //设置Job对应的参数：Mapper输出key和value的类型
        //不需要关注Mapper输入
        //Mapper<LongWritable, Text, Text, IntWritable>
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        //设置Job对应的参数：Reducer输出key和value的类型
        //不需要关注Reducer输入
        //Reducer<Text, IntWritable, Text, IntWritable>
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        //设置Job对应的参数：Mapper输出key和value的类型：作业输入和输出的路径
        FileInputFormat.setInputPaths(job, new Path("input"));
        FileOutputFormat.setOutputPath(job, new Path("output"));

        //提交job
        boolean result = job.waitForCompletion(true);

        System.exit(result ? 0 : -1);

    }

}

 

4、结果输出

问题描述：统计结果区分大小写

解决措施：在WordCountMapper.java中

context.write(new Text(word), new IntWritable(1));

改为

context.write(new Text(word.toLowerCase()), new IntWritable(1));