MapReduce Cross 示例

MapReduce Cross 示例

package com.bsr.cross;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
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;
/**
 * 第一次mr--目的是获取某一人是哪些人的好友
 *
 *
 */
public class Cross {

    //输入：A:B,C,D,F,E,O
    //输出：B->A C->A D->A F->A E->A O->A
    public static class Map extends Mapper<LongWritable, Text, Text, Text>{
        @Override
        protected void map(LongWritable key, Text value,Context context)
                throws IOException, InterruptedException {
            String[] value1=value.toString().split(":");
            String[] value2=value1[1].split(",");
            for (String string : value2) {
                context.write(new Text(string), new Text(value1[0]));
            }
        }

    }
    public static class Reduce extends Reducer<Text, Text, Text, Text>{
        // 输入<B->A><B->E><B->F>....
        // 输出 B A,E,F,J
        @Override
        protected void reduce(Text key, Iterable<Text> value,Context context)
                throws IOException, InterruptedException {
            StringBuffer sb=new StringBuffer();
            for (Text text : value) {
                sb.append(text+",");
            }
            context.write(key, new Text(sb.toString()));
        }

    }

    public static void main(String[] args) throws Exception {
        //读取classpath下的所有xxx-site.xml配置文件，并进行解析
        Configuration conf=new Configuration();
        FileSystem fs = FileSystem.get(configuration);
        String s = "/wc/output3";
        Path path = new Path(s);
        fs.delete(path, true);

        Job job=Job.getInstance(conf);

        //通过主类的类加载器机制获取到本job的所有代码所在的jar包
        job.setJarByClass(Cross.class);

        //指定本job使用的mapper类
        job.setMapperClass(Map.class);

        //指定本job使用的reducer类
        job.setReducerClass(Reduce.class);

        //指定mapper输出的kv数据类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);

        //指定reducer输出的kv数据类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        //指定本job要处理的文件所在的路径
        FileInputFormat.setInputPaths(job, new Path("/wc/data/"));
        FileOutputFormat.setOutputPath(job, new Path("/wc/output3"));

        //将本job向hadoop集群提交执行
        boolean flag=job.waitForCompletion(true);
        System.exit(flag?0:1);

    }

    }
    

进行了逻辑的转换；