新增依賴

    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-common</artifactId>
      <version>2.6.0</version>
    </dependency>
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-hdfs</artifactId>
      <version>2.6.0</version>
    </dependency>
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-mapreduce-client-core</artifactId>
      <version>2.6.0</version>
    </dependency>
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-mapreduce-client-jobclient</artifactId>
      <version>2.6.0</version>
    </dependency>
 

一、jar方式

package Hadoop;
import java.io.IOException;
import java.util.StringTokenizer;
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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
public class WordCount {

    //四個引數，前兩個為輸入<key,value>對，後兩個為輸出<key,value>對;
    //LongWritable、IntWritable、Text可視為Java 的long、int、String替代品;
    public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable>{
        //一個標記單詞個數的常量，值為1，這個常量也可以不定義，在後面程式直接用整數1代替，private final static定義的是常量;
        private final static IntWritable one = new IntWritable(1);
        //充當中間變數，儲存詞;
        private Text word = new Text();
        //map方法，key為偏移量，對value進行拆分，<span style="font-family: Arial, Helvetica, sans-serif;">context為上下文機制;</span>
        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            //對轉換的字串進行分隔;
            StringTokenizer itr = new StringTokenizer(value.toString());
            //利用迴圈函式進行依次處理;
            while (itr.hasMoreTokens()) {
                //返回從當前位置到下一個分隔符的字串;
                word.set(itr.nextToken());
                //如 context.write("hello",1);
                context.write(word, one);
            }
        }
    }

    //四個引數，前兩個為輸入<key,value>對，後兩個為輸出<key,value>對;
    public static class IntSumReducer extends Reducer<Text,IntWritable,Text,IntWritable> {
        //定義一個變數;
        private IntWritable result = new IntWritable();
        //reduce方法，key為如 "hello"，Iterable遍歷所有key的個數;
        public void reduce(Text key, Iterable<IntWritable> values,Context context) throws IOException, InterruptedException {
            //  用於記錄key個數的變數;
            int sum = 0;
            //求key的個數;
            for (IntWritable val : values) {
                sum += val.get();
            }
            //把sum個數存到result中去;
            result.set(sum);
            //如 context.write("hello",7);
            context.write(key, result);
        }
    }

    //主方法;
    public static void main(String[] args) throws Exception {
        //指定作業執行規範;
        Configuration conf = new Configuration();
        //這裡需要配置引數即輸入和輸出的HDFS的檔案路徑
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        if (otherArgs.length < 2) {
            System.err.println("Usage: wordcount <in> [<in>...] <out>");
            System.exit(2);
        }
        //設定Job名稱、執行物件;
        Job job = new Job(conf, "word count");
        job.setJarByClass(WordCount.class);
        //為job設定map類;
        job.setMapperClass(TokenizerMapper.class);
        //為job設定Combiner類;
        job.setCombinerClass(IntSumReducer.class);
        //為job設定 reduce類;
        job.setReducerClass(IntSumReducer.class);
        //設定輸出key型別;
        job.setOutputKeyClass(Text.class);
        //設定輸出value型別;
        job.setOutputValueClass(IntWritable.class);
        //設定輸入路徑;
        for (int i = 0; i < otherArgs.length - 1; ++i) {
            FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
        }
        //設定輸出路徑;
        FileOutputFormat.setOutputPath(job,new Path(otherArgs[otherArgs.length - 1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }

}
 

 生成jar，並將其拷貝到/usr/local/hadoop 目錄下，執行以下命令

hadoop  jar  /usr/local/hadoop/MavenMapReduceHelloWorld-1.0-SNAPSHOT.jar
Hadoop.WordCount /input /output

結果

二、IDEA 遠端執行 

package Hadoop;
import java.io.IOException;
import java.net.URI;
import java.util.StringTokenizer;
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.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.output.FileOutputFormat;

public class WordCount2 {

    //四個引數，前兩個為輸入<key,value>對，後兩個為輸出<key,value>對;
    //LongWritable、IntWritable、Text可視為Java 的long、int、String替代品;
    public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable>{
        //一個標記單詞個數的常量，值為1，這個常量也可以不定義，在後面程式直接用整數1代替，private final static定義的是常量;
        private final static IntWritable one = new IntWritable(1);
        //充當中間變數，儲存詞;
        private Text word = new Text();
        //map方法，key為偏移量，對value進行拆分，<span style="font-family: Arial, Helvetica, sans-serif;">context為上下文機制;</span>
        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            System.out.println("Map key:" + key + ",value:" + value);
            //對轉換的字串進行分隔;
            StringTokenizer itr = new StringTokenizer(value.toString());
            //利用迴圈函式進行依次處理;
            while (itr.hasMoreTokens()) {
                //返回從當前位置到下一個分隔符的字串;
                word.set(itr.nextToken());
                //如 context.write("hello",1);
                context.write(word, one);
            }
        }
    }

    //四個引數，前兩個為輸入<key,value>對，後兩個為輸出<key,value>對;
    public static class IntSumReducer extends Reducer<Text,IntWritable,Text,IntWritable> {
        //定義一個變數;
        private IntWritable result = new IntWritable();
        //reduce方法，key為如 "hello"，Iterable遍歷所有key的個數;
        public void reduce(Text key, Iterable<IntWritable> values,Context context) throws IOException, InterruptedException {
            StringBuffer sb = new StringBuffer();
            sb.append("Reduce key:" + key + ",value:");
            //  用於記錄key個數的變數;
            int sum = 0;
            //求key的個數;
            for (IntWritable val : values) {
                sb.append(val.get()+" ");
                sum += val.get();
            }
            System.out.println(sb.toString());
            //把sum個數存到result中去;
            result.set(sum);
            //如 context.write("hello",7);
            context.write(key, result);
        }
    }

    //主方法;
    public static void main(String[] args) throws Exception {
        //指定作業執行規範;
        Configuration conf = new Configuration();

        conf.set("fs.defaultFS", "hdfs://192.168.255.128:9000");
        System.setProperty("HADOOP_USER_NAME", "root");
        //hadoop2.6 資料夾放在 hadoop2.6.rar 中
        System.setProperty("hadoop.home.dir", "E:/hadoop2.6");
        final String OUTPUT_PATH="hdfs://192.168.255.128:9000/output";
        Path outpath = new Path(OUTPUT_PATH);

        //清空原先的資料
        FileSystem fs = FileSystem.get(new URI(OUTPUT_PATH),conf);
        if(fs.exists(outpath)){
            fs.delete(outpath,true);
        }

        //設定Job名稱、執行物件;
        Job job = new Job(conf, "word count");
        job.setJarByClass(WordCount.class);
        //為job設定map類;
        job.setMapperClass(TokenizerMapper.class);
        //為job設定Combiner類;
        job.setCombinerClass(IntSumReducer.class);
        //為job設定 reduce類;
        job.setReducerClass(IntSumReducer.class);
        //設定輸出key型別;
        job.setOutputKeyClass(Text.class);
        //設定輸出value型別;
        job.setOutputValueClass(IntWritable.class);

        //設定輸入路徑
        FileInputFormat.addInputPath(job, new Path("hdfs://192.168.255.128:9000/input"));
        //設定輸出路徑;
        FileOutputFormat.setOutputPath(job,new  Path("hdfs://192.168.255.128:9000/output"));

        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }

}
 

將 hadoop2.6/bin 資料夾下面 的hadoop.dll拷貝到C:\Windows\ System32