hadoop程序MapReduce之SingletonTableJoin

需求：单表关联问题。从文件中孩子和父母的关系挖掘出孙子和爷奶关系

样板：child-parent.txt

xiaoming daxiong

daxiong alice

daxiong jack

输出：xiaoming alice

xiaoming jack

分析设计：

mapper部分设计：

1、<k1,k1>k1代表：一行数据的编号位置，v1代表：一行数据。

2、左表：<k2,v2>k2代表：parent名字，v2代表：(1,child名字)，此处1：代表左表标志。

3、右表：<k3,v3>k3代表：child名字，v3代表：(2，parent名字)，此处2：代表右表标志。

reduce部分设计：

4、<k4,v4>k4代表：相同的key,v4代表：list<String>

5、求笛卡尔积<k5,v5>:k5代表：grandChild名字，v5代表：grandParent名字。

程序部分：

SingletonTableJoinMapper类

package com.cn.singletonTableJoin;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class SingletonTableJoinMapper extends Mapper<Object, Text, Text, Text> {
    @Override
    protected void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context)
            throws IOException, InterruptedException {
        String childName = new String();
        String parentName = new String();
        String relationType = new String();
        String[] values=new String[2];
        int i = 0;
        StringTokenizer itr = new StringTokenizer(value.toString());
        while(itr.hasMoreElements()){
            values[i] = itr.nextToken();
            i++;
        }
        if(values[0].compareTo("child") != 0){
            childName  = values[0];
            parentName = values[1];
            relationType = "1";
            context.write(new Text(parentName), new Text(relationType+" "+childName));
            relationType = "2";
            context.write(new Text(childName), new Text(relationType+" "+parentName));
        }
    }
}

SingletonTableJoinReduce类：

package com.cn.singletonTableJoin;

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

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

public class SingletonTableJoinReduce extends Reducer<Text, Text, Text, Text> {
    @Override
    protected void reduce(Text key, Iterable<Text> values, Reducer<Text, Text, Text, Text>.Context context)
            throws IOException, InterruptedException {
        List<String> grandChild = new ArrayList<String>();
        List<String> grandParent = new ArrayList<String>();
        Iterator<Text> itr = values.iterator();
        while(itr.hasNext()){
            String[] record = itr.next().toString().split(" ");
            if(0 == record[0].length()){
                continue;
            }
            if("1".equals(record[0])){
                grandChild.add(record[1]);
            }else if("2".equals(record[0])){
                grandParent.add(record[1]);
            }
        }
        if(0 != grandChild.size() && 0 != grandParent.size()){
            for(String grandchild : grandChild){
                for(String grandparent : grandParent){
                    context.write(new Text(grandchild), new Text(grandparent));
                }
            }
        }
    }
}

SingletonTableJoin类

package com.cn.singletonTableJoin;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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;
import org.apache.hadoop.util.GenericOptionsParser;

/**
 * 单表关联
 * @author root
 *
 */
public class SingletonTableJoin {
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        if (otherArgs.length != 2) {
           System.err.println("Usage: SingletonTableJoin  ");
           System.exit(2);
        }
        //创建一个job
        Job job = new Job(conf, "SingletonTableJoin");
        job.setJarByClass(SingletonTableJoin.class);

        //设置文件的输入输出路径
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));

        //设置mapper和reduce处理类
        job.setMapperClass(SingletonTableJoinMapper.class);
        job.setReducerClass(SingletonTableJoinReduce.class);

      //设置输出key-value数据类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

       //提交作业并等待它完成
       System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

把总结当成一种习惯。