这篇博客，给大家，体会不一样的版本编程。

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

代码

1 package zhouls.bigdata.myMapReduce.wordcount3; 2  3 import java.io.IOException; 4  5 import org.apache.hadoop.io.IntWritable; 6 import org.apache.hadoop.io.LongWritable; 7 import org.apache.hadoop.io.Text; 8 import org.apache.hadoop.mapreduce.Mapper; 9 import org.apache.hadoop.util.StringUtils;10 11 public class WordCountMapper extends Mapper
     
      {12 13 //该方法循环调用，从文件的split中读取每行调用一次，把该行所在的下标为key，该行的内容为value14 protected void map(LongWritable key, Text value,15 Context context)16 throws IOException, InterruptedException {17 String[] words = StringUtils.split(value.toString(), ' ');18 for(String w :words){19 context.write(new Text(w), new IntWritable(1));20 }21 }22 }
     

 

 

 

1 package zhouls.bigdata.myMapReduce.wordcount3; 2  3 import java.io.IOException; 4  5 import org.apache.hadoop.io.IntWritable; 6 import org.apache.hadoop.io.Text; 7 import org.apache.hadoop.mapreduce.Reducer; 8  9 public class WordCountReducer extends Reducer
     
      {10 11 //每组调用一次，这一组数据特点：key相同，value可能有多个。12 protected void reduce(Text arg0, Iterable
      
        arg1,13 Context arg2)14 throws IOException, InterruptedException {15 int sum =0;16 for(IntWritable i: arg1){17 sum=sum+i.get();18 }19 arg2.write(arg0, new IntWritable(sum));20 }21 }
      
     

 

 

 

1 package zhouls.bigdata.myMapReduce.wordcount3; 2  3  4 import org.apache.hadoop.conf.Configuration; 5 import org.apache.hadoop.fs.FileSystem; 6 import org.apache.hadoop.fs.Path; 7 import org.apache.hadoop.io.IntWritable; 8 import org.apache.hadoop.io.Text; 9 import org.apache.hadoop.mapreduce.Job;10 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;11 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;12 13 public class RunJob {14 15 public static void main(String[] args) {16 Configuration config =new Configuration();17 18 try {19 FileSystem fs =FileSystem.get(config);20 21 Job job =Job.getInstance(config);22 job.setJarByClass(RunJob.class);23 24 job.setJobName("wc");25 26 job.setMapperClass(WordCountMapper.class);27 job.setReducerClass(WordCountReducer.class);28 29 job.setMapOutputKeyClass(Text.class);30 job.setMapOutputValueClass(IntWritable.class);31 32 FileInputFormat.addInputPath(job, new Path("./data/wc.txt"));33 34 Path outpath =new Path("./out/WordCountout");35 if(fs.exists(outpath)){36 fs.delete(outpath, true);37 }38 FileOutputFormat.setOutputPath(job, outpath);39 40 boolean f= job.waitForCompletion(true);41 if(f){42 System.out.println("job任务执行成功");43 }44 } catch (Exception e) {45 e.printStackTrace();46 }47 }48 }