一 需求

这个案例的需求很简单

现在这里有一个文本wordcount.txt，内容如下

现要求你使用 mapreduce 框架统计每个单词的出现个数 

这样一个案例虽然简单但可以让新学习大数据的同学熟悉 mapreduce 框架

二 准备工作

（1）创建一个 maven 工程，maven 工程框架可以选择quickstart

（2）在properties中添加 hadoop.version，导入依赖，pom.xml内容如下

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><groupId>org.example</groupId><artifactId>maven_hadoop</artifactId><version>1.0-SNAPSHOT</version><dependencies><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>4.11</version><scope>test</scope></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-common</artifactId><version>${hadoop.version}</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-hdfs</artifactId><version>${hadoop.version}</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-mapreduce-client-core</artifactId><version>${hadoop.version}</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-mapreduce-client-common</artifactId><version>${hadoop.version}</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-client</artifactId><version>${hadoop.version}</version></dependency></dependencies><properties><maven.compiler.source>8</maven.compiler.source><maven.compiler.target>8</maven.compiler.target><hadoop.version>3.1.3</hadoop.version></properties></project>

（3）准备数据，创建两个文件夹 in，out（一个是输入文件，一个是输出文件），输入文件放在 in 文件夹中

三 编写 WordCountMapper 类

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;import java.io.IOException;//                                              <0,       hello java, hello, 1       >
//                                              <0,       hello java, java, 1       >
//  alt + ins
public class WordCountMapper extends Mapper<LongWritable, Text,Text, IntWritable> {Text text = new Text();IntWritable intWritable =  new IntWritable();@Overrideprotected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {System.out.println("WordCountMap stage Key:"+key+"  Value:"+value);String[] words = value.toString().split(" ");  // "hello java"--->[hello,java]for (String word :words) {text.set(word);intWritable.set(1);context.write(text,intWritable);   //<hello,1>,<java,1>}}
}

四 编写 WordCountReducer 类

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;import java.io.IOException;public class WordCountReduce extends Reducer<Text, IntWritable, Text, LongWritable> {@Overrideprotected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {System.out.println("Reduce stage Key:" + key + "  Values:" + values.toString());int count = 0;for (IntWritable intWritable :values) {count+=intWritable.get();}LongWritable longWritable = new LongWritable(count);System.out.println("ReduceResult key:"+key+" resultValue:"+longWritable.get());context.write(key,longWritable);}
}

五 编写WordCountDriver 类

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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import java.io.IOException;public class WordCountDriver {public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {Configuration conf = new Configuration();Job job = Job.getInstance(conf);job.setJarByClass(WordCountDriver.class);// 设置job的map阶段 工作任务job.setMapperClass(WordCountMapper.class);job.setMapOutputKeyClass(Text.class);job.setMapOutputValueClass(IntWritable.class);// 设置job的reduce阶段 工作任务job.setReducerClass(WordCountReduce.class);job.setOutputKeyClass(Text.class);job.setOutputValueClass(LongWritable.class);// 指定job map阶段的输入文件的路径FileInputFormat.setInputPaths(job, new Path("D:\\bigdataworkspace\\kb23\\hadoopstu\\in\\wordcount.txt"));// 指定job reduce阶段的输出文件路径Path path = new Path("D:\\bigdataworkspace\\kb23\\hadoopstu\\out1");FileSystem fileSystem = FileSystem.get(path.toUri(), conf);if (fileSystem.exists(path))fileSystem.delete(path,true);FileOutputFormat.setOutputPath(job, path);// 启动jobjob.waitForCompletion(true);}
}