Hadoop MapReduce编程 API入门系列之wordcount版本3（七）

　　这篇博客，给大家，体会不一样的版本编程。

代码

 package zhouls.bigdata.myMapReduce.wordcount3;

 import java.io.IOException;

 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 org.apache.hadoop.util.StringUtils;

 public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable>{

 //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value
 protected void map(LongWritable key, Text value,
 Context context)
 throws IOException, InterruptedException {
 String[] words = StringUtils.split(value.toString(), ' ');
 for(String w :words){
 context.write(new Text(w), new IntWritable(1));
 }
 }
 }

 package zhouls.bigdata.myMapReduce.wordcount3;

 import java.io.IOException;

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

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

 //每组调用一次，这一组数据特点：key相同，value可能有多个。
 protected void reduce(Text arg0, Iterable<IntWritable> arg1,
 Context arg2)
 throws IOException, InterruptedException {
 int sum =0;
 for(IntWritable i: arg1){
 sum=sum+i.get();
 }
 arg2.write(arg0, new IntWritable(sum));
 }
 }

 package zhouls.bigdata.myMapReduce.wordcount3;

 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.lib.input.FileInputFormat;
 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

 public class RunJob {

 public static void main(String[] args) {
 Configuration config =new Configuration();

 try {
 FileSystem fs =FileSystem.get(config);

 Job job =Job.getInstance(config);
 job.setJarByClass(RunJob.class);

 job.setJobName("wc");

 job.setMapperClass(WordCountMapper.class);
 job.setReducerClass(WordCountReducer.class);

 job.setMapOutputKeyClass(Text.class);
 job.setMapOutputValueClass(IntWritable.class);

 FileInputFormat.addInputPath(job, new Path("./data/wc.txt"));

 Path outpath =new Path("./out/WordCountout");
 if(fs.exists(outpath)){
 fs.delete(outpath, true);
 }
 FileOutputFormat.setOutputPath(job, outpath);

 boolean f= job.waitForCompletion(true);
 if(f){
 System.out.println("job任务执行成功");
 }
 } catch (Exception e) {
 e.printStackTrace();
 }
 }
 }