MongoDB 之MapReduce统计关键字频率测试
测试环境:windows xp

  Operating System: Windows XP Professional (5.1, Build 2600) Service Pack 3 (2600.xpsp_sp3_gdr.101209-1647)
  Language: Chinese (Regional Setting: Chinese)
  Processor: Pentium(R) Dual-Core  CPU      E5500  @ 2.80GHz (2 CPUs)
  Memory: 3292MB RAM
测试结果：
   1079844 条数据统计出10957个关键字排序取前100条记录，总耗时:308578毫秒  

测试程序：

import java.io.BufferedReader;
import java.io.FileReader;
import java.net.UnknownHostException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;

import com.mongodb.BasicDBObject;
import com.mongodb.DB;
import com.mongodb.DBCollection;
import com.mongodb.DBCursor;
import com.mongodb.DBObject;
import com.mongodb.MapReduceCommand;
import com.mongodb.MapReduceOutput;
import com.mongodb.Mongo;
import com.mongodb.MongoException;

/**
 * 
 */

/**
 * @author songlianjun
 *
 */
public class Test4MongoDb {

	/**
	 * @param args
	 */
	public static void main(String[] args) {
		// TODO Auto-generated method stub
		//insertTestKeywordLog();

		calculateSearchKeyword();

	}

	/**
	 * 生成测试数据
	 */
	private static void insertTestKeywordLog() {
		List<String> keyWordList = new ArrayList<String>();
		try {
			BufferedReader reader = new BufferedReader(new FileReader(
					"d:\\pinyin.txt"));
			String line = null;
			Random ran = new Random(System.currentTimeMillis());
			Mongo m;
			int totalRows = 0;
			long start = 0;
			long end = 0;
			m = new Mongo("localhost", 9999);
			DB db = m.getDB("test");
			DBCollection collection = db.getCollection("t_log");
			String month = "02";
			String year = "2010";
			start = System.currentTimeMillis();
			while ((line = reader.readLine()) != null) {

				int insertCount = ran.nextInt(100);
				if (insertCount == 0) {
					insertCount = 1;
				}
				totalRows += insertCount;
				for (int i = 0; i < insertCount; i++) {

					DBObject record = new BasicDBObject();
					record.put("id", System.currentTimeMillis());
					record.put("keyword", line);

					int day = ran.nextInt(28);
					if (day == 0) {
						day = 1;
					}
					record.put("dd", year + "-" + month
							+ (day < 10 ? "-0" + day : "-" + day));
					collection.save(record);

				}
			}

			end = System.currentTimeMillis();
			System.out.println("insert time =" + (end - start) + " row count="
					+ totalRows);

		} catch (Exception e) {
			// TODO Auto-generated catch block
			e.printStackTrace();
		}
	}

	/**
	 * 统计查询关键字频率
	 */
	private static void calculateSearchKeyword() {
		long start = 0;
		long end = 0;
		Mongo m;
		try {
			m = new Mongo("localhost", 9999);
			DB db = m.getDB("test");
			DBCollection collection = db.getCollection("t_log");

			DBObject newDB = new BasicDBObject();
			newDB.put("max", 100000);

			String collectionName = "t_log_result_"
					+ System.currentTimeMillis();
			DBCollection resultCollection = db.createCollection(collectionName,
					newDB);

			//创建统计数量索引
			DBObject indexObject = new BasicDBObject();
			indexObject.put("hitCount", -1);
			resultCollection.createIndex(indexObject);
			//DBCollection resultCollection = db.getCollection("t_log_result_"+System.currentTimeMillis());
			start = System.currentTimeMillis();

			DBObject dbKey = new BasicDBObject();
			dbKey.put("dd", true);
			//查询符合条件的数据
			DBObject condition = new BasicDBObject();
			condition.put("dd", new BasicDBObject("$gte", "2010-02-01").append(
					"$lte", "2010-02-28"));

			//定义map
			String map = "function() {   key=this.keyword; "
					+ "		emit(key,{'count':1});  " + "}";
			//定义reduce
			String reduce = " function r( key, values ) { " + "	  var count=0;"
					+ "	  for ( var i = 0; i < values.length; i++ ){"
					+ "	      count += values[i].count;" + "	  }"
					+ " return count;} ";
			///Map<String,Object> scope =