1. 程式人生 > >資料探勘--協同過濾演算法,基於集合交集相似性計算的mapreduce演算法設計

資料探勘--協同過濾演算法,基於集合交集相似性計算的mapreduce演算法設計



第一個過程程的mapreduce函式:

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


public class MapReduce extends MapperReduce{

	public MapReduce(){
		super();
	}
	
	public void printf(List<String> list1,List<String> list2) throws IOException{
		if((!list1.isEmpty()) && (!list2.isEmpty())){
			Iterator<String> Iter1=list1.iterator();
			while(Iter1.hasNext()){
				String tmp1=Iter1.next();
				Iterator<String> Iter2=list2.iterator();
				while(Iter2.hasNext()){
					String tmp2=Iter2.next();
					WriteReducer(tmp1,tmp2);
				}
			}
		}
	}
	
	//map函式開始
		public void Mapper(String key,String value) throws IOException{
			//key為行偏移量,value為每一行的值
			String[] count=value.split(" ");
			if(!count[1].trim().equals("")){
				WriteMaper(count[1].trim(),count[0].trim()+" "+"1");
				WriteMaper(count[1].trim(),count[0].trim()+" "+"2");
			}
		}
	//map函式結束
		
	//reduce函式開始	
		public void Reducer(String key,Iterator<String> value) throws IOException{
			List<String> list1=new ArrayList<String>();
			List<String> list2=new ArrayList<String>();
			while(value.hasNext()){
				String tmp=value.next();
				String[] tmp1=tmp.split(" ");
				if(tmp1[1].equals("1")){
					list1.add(tmp1[0]);
				}else{
					list2.add(tmp1[0]);
				}
			}
			printf(list1,list2);
		}
	//reduce函式結束
	public static void main(String[] args) throws IOException {
		MapReduce a=new MapReduce();
		a.IterMapper();
		a.IterReducer();
	}
}

本程式例項是:單表自連線,連線欄位是 user


輸入:

star1 user1
star2 user1
star3 user1
star3 user2

輸出:

star1 star1
star1 star2
star1 star3
star2 star1
star2 star2
star2 star3
star3 star1
star3 star2
star3 star3
star3 star3

第二個過程程的mapreduce函式:

import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Set;


public class MapReduce extends MapperReduce{

	public MapReduce(){
		super();
	}
	
	
	//map函式開始
		public void Mapper(String key,String value) throws IOException{
			String[] content=value.split(" ");
			WriteMaper(content[0],content[1]);
		}
	//map函式結束
		
	//reduce函式開始	
		public void Reducer(String key,Iterator<String> value) throws IOException{
			List<String> list=new ArrayList<String>();
			while(value.hasNext()){
				list.add(value.next());
			}
			Set<String> set = new HashSet<String>(list);
			Map<String,Integer> map=new HashMap<String,Integer>();
			Iterator<String> IterSet=set.iterator();
			while(IterSet.hasNext()){
				map.put(IterSet.next(),0);
			}
			for(int i=0;i<list.size();i++){
				map.put(list.get(i),map.get(list.get(i))+1);
			}
			Iterator<String> It = map.keySet().iterator();
			while(It.hasNext())
			{   
				String tmp=It.next();
				if(!tmp.equals(key)){
					WriteReducer(key,tmp+" "+String.valueOf(((float)map.get(tmp))/map.get(key)));
				}
			    }
		}
	//reduce函式結束
	public static void main(String[] args) throws IOException {
		MapReduce a=new MapReduce();
		a.IterMapper();
		a.IterReducer();
	}
}

輸入:

star1 star1star1 star2star1 star3star2 star1star2 star2star2 star3star3 star1star3 star2star3 star3star3 star3

輸出:

star1 star2 1.0

star1 star3 1.0

star2 star1 1.0

star2 star3 1.0

star3 star1 0.5

star3 star2 0.5