向MapReduce转换：生成用户向量

时间：2021-11-14 18:23:07

分两部分：

<span style="font-size:18px;">/***

 * @author YangXin

 * @date 2016/2/21

 * @ info 主要功能是mahout实现解析Wikipedia链接文件的Mapper接口

 */

package unitSix;

import java.io.IOException;

import java.util.regex.Matcher;

import java.util.regex.Pattern;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.mahout.math.VarLongWritable;

public class WikipediaToItemPrefsMapper extends Mapper<LongWritable, Text, VarLongWritable, VarLongWritable>{

	private static final Pattern NUMBERS = Pattern.compile("(\\d+)");

	public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{

		String line = value.toString();

		Matcher m = NUMBERS.matcher(line);

		//定位用户ID

		m.find();

		VarLongWritable userID = new VarLongWritable(Long.parseLong(m.group()));

		VarLongWritable itemID = new VarLongWritable();

		while(m.find()){

			itemID.set(Long.parseLong(m.group()));

			//为每一个物品ID生成用户-物品对

			context.write(userID, itemID);

		}

	}

}</span>



<strong><span style="font-size:18px;">/***

 * @author YangXin

 * @info 功能是mahout实现从用户物品偏好中生成Vector的reducer接口

 */

package unitSix;

import java.io.IOException;

import org.apache.hadoop.mapreduce.Reducer;

import org.apache.mahout.math.RandomAccessSparseVector;

import org.apache.mahout.math.VarLongWritable;

import org.apache.mahout.math.Vector;

import org.apache.mahout.math.VectorWritable;

public class WikipediaToUserVectorReducer extends Reducer<VarLongWritable, VarLongWritable, VarLongWritable, VectorWritable>{

	public void reduce(VarLongWritable userID, Iterable<VarLongWritable> itemPrefs, Context context) throws IOException, InterruptedException{

		Vector userVector = new RandomAccessSparseVector(Integer.MAX_VALUE, 100);

		for(VarLongWritable itemPref : itemPrefs){

			userVector.set((int)itemPref.get(), 1.0f);

		}

		context.write(userID, new VectorWritable(userVector));

	}

}

</span></strong>

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