hadoop--mapreduce代码之单表关联

package com.hadoop.sample;

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

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 {
	private 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;
			while(line.charAt(i) != ' '){
				i++;
			}
			String[] values = {line.substring(0,i),line.substring(i+1)};
			if(values[0].compareTo("child") != 0){
				childname = values[0];
				parentname = values[1];
				relationtype = "1";//左右表区分标志
				context.write(new Text(values[1]), new Text(relationtype + "+" +childname+"+"+parentname));//左表
				relationtype = "2";
				context.write(new Text(values[0]), new Text(relationtype + "+" +childname+"+"+parentname));//右表
			}
		}
	}
	public static class Reduce extends Reducer<Text,Text,Text,Text>{
		public void reduce(Text key,Iterable<Text> values,Context context) throws IOException,InterruptedException{
			if(time == 0){//输出表头
				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();
				//获取value-list中value的child
				while(record.charAt(i) != '+'){
					childname = childname + record.charAt(i);
					i++;
				}
				i = i+1;
				//获取value-list中value的parent
				while(i<len){
					parentname = parentname + record.charAt(i);
					i++;
				}
				//左表，取出child放入grandchild
				if(relationtype == '1'){
					grandchild[grandchildnum]=childname;
					grandchildnum++;
				}else{//右表，取出parent放入grandparent
					grandparent[grandparentnum]=parentname;
					grandparentnum++;
				}
				
			}
			//grandchild和grandparent数组求笛卡尔积
			if(grandparentnum!=0&&grandchildnum!=0){
				for(int m=0;m<grandchildnum;m++){
					for(int n=0;n<grandparentnum;n++){
						context.write(new Text(grandchild[m]), new Text(grandparent[n]));
					}
				}
			}
		}
	}
	/**
	 * @param args
	 */
	public static void main(String[] args) throws Exception{
		// TODO Auto-generated method stub
		Configuration conf = new Configuration();
		String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();
		if(otherArgs.length != 2){
			System.err.println("Usage WordCount <int> <out>");
			System.exit(2);
		}
		Job job = new Job(conf,"single table join");
		job.setJarByClass(STJoin.class);
		job.setMapperClass(Map.class);
		job.setCombinerClass(Reduce.class);
		job.setReducerClass(Reduce.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(Text.class);
		FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
		FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}

}

评论

1 楼 good_ovo 2015-04-27  

有读取的文件吗？