import java.io.IOException;

import java.util.*;

import org.apache.hadoop.conf.Configuration;

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.output.FileOutputFormat;

import org.apache.hadoop.util.GenericOptionsParser;

public  class STjoin {

     public  static  int  time = 0;

    /*

     * map将输出分割child和parent，然后反序输出一次作为左表，

     * 正序输出一次作为右表，需要注意的是在输出的value中必须

     * 加上左右表的区别标识。

     */

     public  static  class Map  extends Mapper<Object, Text, Text, Text> {

        // 实现map函数

         public  void map(Object key, Text value, Context context)

                 throws IOException, InterruptedException {

            String childname =  new String();// 孩子名称

            String parentname =  new String();// 父母名称

            String relationtype =  new String();// 左右表标识

            // 输入的一行预处理文本

            StringTokenizer itr= new StringTokenizer(value.toString());

            String[] values= new String[2];

             int i=0;

             while(itr.hasMoreTokens()){

                values[i]=itr.nextToken();

                i++;

            }

             if (values[0].compareTo("child") != 0) {

                childname = values[0];

                parentname = values[1];

                // 输出左表

                relationtype = "1";

                context.write( new Text(values[1]),  new Text(relationtype +

                        "+"+ childname + "+" + parentname));

                // 输出右表

                relationtype = "2";

                context.write( new Text(values[0]),  new Text(relationtype +

                        "+"+ childname + "+" + parentname));

            }

        }

    }

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

        // 实现reduce函数

         public  void reduce(Text key, Iterable<Text> values, Context context)

                 throws IOException, InterruptedException {

            // 输出表头

             if (0 ==  time) {

                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 (0 == len) {

                     continue;

                }

                // 取得左右表标识

                 char relationtype = record.charAt(0);

                // 定义孩子和父母变量

                String childname =  new String();

                String parentname =  new String();

                // 获取value-list中value的child

                 while (record.charAt(i) != '+') {

                    childname += record.charAt(i);

                    i++;

                }

                i = i + 1;

                // 获取value-list中value的parent

                 while (i < len) {

                    parentname += record.charAt(i);

                    i++;

                }

                // 左表，取出child放入grandchildren

                 if ('1' == relationtype) {

                    grandchild[grandchildnum] = childname;

                    grandchildnum++;

                }

                // 右表，取出parent放入grandparent

                 if ('2' == relationtype) {

                    grandparent[grandparentnum] = parentname;

                    grandparentnum++;

                }

            }

            // grandchild和grandparent数组求笛卡尔儿积

             if (0 != grandchildnum && 0 != grandparentnum) {

                 for ( int m = 0; m < grandchildnum; m++) {

                     for ( int n = 0; n < grandparentnum; n++) {

                        // 输出结果

                        context.write( new Text(grandchild[m]),  new Text(grandparent[n]));

                    }

                }

            }

        }

    }

     public  static  void main(String[] args)  throws Exception {

        Configuration conf =  new Configuration();

        conf.set("mapred.job.tracker", "192.168.1.2:9001");

        String[] ioArgs =  new String[] { "STjoin_in", "STjoin_out" };

        String[] otherArgs =  new GenericOptionsParser(conf, ioArgs).getRemainingArgs();

         if (otherArgs.length != 2) {

            System. err.println("Usage: Single Table Join <in> <out>");

            System. exit(2);

        }

        Job job =  new Job(conf, "Single Table Join");

        job.setJarByClass(STjoin. class);

        // 设置Map和Reduce处理类

        job.setMapperClass(Map. class);

        job.setReducerClass(Reduce. class);

        // 设置输出类型

        job.setOutputKeyClass(Text. class);

        job.setOutputValueClass(Text. class);

        // 设置输入和输出目录

        FileInputFormat. addInputPath(job,  new Path(otherArgs[0]));

        FileOutputFormat. setOutputPath(job,  new Path(otherArgs[1]));

        System. exit(job.waitForCompletion( true) ? 0 : 1);

    }

}