Hadoop--MapReduce實現WordCount全步驟

原創

2020-06-18 23:11

新建maven項目
1. +Create New Project… ->Maven -> Next
2. 填寫好GroupId和ArtifactId 點擊Next -> Finish
編寫wordcount項目
1. 建立項目結構目錄：右鍵java -> New -> package 輸入package路徑（本例是com.hadoop.wdcount）建立package。類似的方式在創建好的package下建立三個類WordcountMain、WordcountMapper、WordcountReducer
  
  2、編寫pom.xml配置（引入要用到的hadoop的jar包）

<?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>sa.hadoop</groupId>
    <artifactId>wordcount</artifactId>
    <version>1.0-SNAPSHOT</version>

    <dependencies>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>2.7.7</version>
<!--    我們用的是2.7.7版本的hadoop   -->
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>2.7.7</version>
        </dependency>
		<dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-mapreduce-client-common</artifactId>
            <version>2.7.7</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-mapreduce-client-core</artifactId>
            <version>2.7.7</version>
        </dependency>
    </dependencies>
    
</project>

3、編寫項目代碼
完成剛剛建立的三個類中的邏輯實現。
(1) WordcountMapper.java

package com.hadoop.wdcount;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;

import java.io.IOException;

public class WordcountMapper extends org.apache.hadoop.mapreduce.Mapper<LongWritable,Text,Text,IntWritable> {


    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String line=value.toString();
        String[] words=line.split(" ");
        for (String word:words){
            context.write(new Text(word),new IntWritable(1));
        }
    }
}

(2)WordcountReducer.java

package com.hadoop.wdcount;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;
import java.util.Iterator;

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

    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        Integer counts=0;
        for (IntWritable value:values){
            counts+=value.get();
        }
        context.write(key,new IntWritable(counts));
    }
}

(3)WordcountMain.java

package com.hadoop.wdcount;

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;

public class WordcountMain {
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf, "wordcount");
        job.setJarByClass(WordcountMain.class);
        job.setMapperClass(WordcountMapper.class);
        job.setReducerClass(WordcountReducer.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        FileInputFormat.setInputPaths(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        boolean flag = job.waitForCompletion(true);
        if (!flag) {
            System.out.println("wordcount failed!");
        }
    }
}

將項目打包成jar
1. 右鍵項目名稱 -> Open Module Settings
2. Artifacts -> + -> JAR -> From modules with dependencies…
3. 填寫Main Class（點擊…選擇WordcountMain），然後選擇extract to the target JAR，點擊OK。
4. 勾選include in project build ，其中Output directory爲最後的輸出目錄，下面output layout是輸出的各jar包，點擊ok
5. 點擊菜單Build——>Build Aritifacts…
6. 選擇Build，結果可到前面4的output目錄查看或者項目結構中的out目錄
執行驗證（這裏採用win環境下的hadoop2.7.6作爲例子，wsl暫時未驗證）
1. 先在創建jar包路徑下（C:\Users\USTC\Documents\maxyi\Java\wordcount\out\artifacts\wordcount_jar）建立一個input1.txt文檔，並添加內容“I believe that I will succeed!”並保存。等會兒要將該txt文件上傳到hadoop。
2. 運行hadoop打開所有節點
  cd hadoop-2.7.6/sbin
  start-all.cmd
3. 運行成功後，來到之前創建的jar包路徑，將編寫好的txt文件上傳到hadoop
  cd /
  cd C:\Users\USTC\Documents\maxyi\Java\wordcount\out\artifacts \wordcount_jar
  hadoop fs -put ./input1.txt /input1
  可以用以下代碼查看是否上傳成功。
  hadoop fs -ls /
  4、刪除wordcount.jar/META-INF/LICENSE，否則不能創建hadoop運行時不能創建license，會報錯。
  5、運行wordcount
  hadoop jar wordcount.jar com.hadoop.wdcount.WordcountMain /input1 /output2
  jar 命令後有四個參數，
  第一個wordcount.jar是打好的jar包
  第二個com.hadoop.wdcount.WordcountMain是java工程總編寫的主類，這裏要包含package路徑
  第三個/input1是剛剛上傳的輸入
  第四個/output2是wordcount的輸出（一定要新建，不能重用之前建立的）
  6、下載輸出文件查看結果是否正確
  hadoop fs -get /output2