MapReduce单表关联学习~

首先考虑表的自连接，其次是列的设置，最后是结果的整理.

文件内容：

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

import java.io.IOException;
import java.util.Iterator;
import java.util.Objects;

public class STjoin extends Configured implements Tool {
    public static int time = 0;
　　//map将输入分割成child和parent,然后正序输出一次作为右表，反序输出一次作为左表　　//需要注意的是在输出的value中必须加上左右表区别标志
    public static class Map extends Mapper<Object,Text,Text,Text>{

        public void map(Object key,Text value,Context context) throws IOException,
                InterruptedException{
            String childname = new String();
            String parentname = new String();
            String relationtype = new String();
            String line = value.toString();
            int i = 0;　　　　　　　//文件以空格分隔
            while(line.charAt(i) != ‘ ‘){
                i++;
            }　　　　　　　//拆分child 和 parent
            String[] values = {line.substring(0,i),line.substring(i+1)};
            if(values[0].compareTo("child") != 0){
                childname = values[0];
                parentname = values[1];　　　　　　　　　//左右表区分标志
                relationtype = "1";
                context.write(new Text(values[1]),new Text(relationtype + "+" + childname + "+" + parentname));

                relationtype = "2";
                context.write(new Text(values[0]),new Text(relationtype + "+" + childname + "+" + parentname));
            }
        }
    }

    public static class Reduce extends Reducer<Text,Text,Text,Text>{

        public void reduce(Text key,Iterable<Text> values,Context context) throws IOException,InterruptedException{　　　　　　　　//输出表头
            if(time == 0){
                context.write(new Text("grandchild"),new Text("grandparent"));
                time++;
            }
            int grandchildnum = 0;
            String grandchild[] = new String[10];
            int grandparentnum = 0;
            String grandparent[] = new String[10];
            Iterator ite = values.iterator();

            while(ite.hasNext()){
                String record = ite.next().toString();
                int len = record.length();
                int i = 2;
                if(len == 0){
                    continue;
                }
                char relationtype = record.charAt(0);
                String childname = new String();
                String parentname = new String();

                while(record.charAt(i) != ‘+‘){
                    childname = childname + record.charAt(i);
                    i++;
                }
                i = i+1;

                while(i<len){
                    parentname = parentname + record.charAt(i);
                    i++;
                }

                if(relationtype == ‘1‘) {
                    grandchild[grandchildnum] = childname;
                    ;
                    grandchildnum++;
                }else{
                    grandparent[grandparentnum] = parentname;
                    grandparentnum++;
                }

            }

            if(grandparentnum != 0 && grandchildnum != 0){
                    for(int m = 0;m<grandchildnum;m++){
                        for(int n = 0;n<grandparentnum;n++){
                            System.out.println(grandchild[m] + "  " + grandparent[n]);
                            context.write(new Text(grandchild[m]),new Text(grandparent[n]));
                        }
                    }
            }

        }
    }

    public  int run(String[] args) throws Exception{
        Configuration aaa = new Configuration();
        Job job = Job.getInstance(aaa);
        String InputPaths = "/usr/local/idea-IC-139.1117.1/Hadoop/out/datainput/child-parent.txt";
        String OutputPath = "/usr/local/idea-IC-139.1117.1/Hadoop/out/dataout/";

        job.setJarByClass(Sort.class);
        job.setJobName("Sort");

        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);
        FileInputFormat.setInputPaths(job, new Path(InputPaths));
        FileOutputFormat.setOutputPath(job, new Path(OutputPath));

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.class);
        boolean success = job.waitForCompletion(true);
        return success ? 0 : 1;

    }

    public static void main(String[] args) throws Exception{
            int ret = ToolRunner.run(new STjoin(), args);
            System.exit(ret);
    }
}

输出结果：

参考：《Hadoop实战》