java操作mongodb(分页优化)

前面我们提到过，大数据量分页时，skip如果跳过大量的数据会很慢，这里针对这一情况，我们优化一下分页。

看代码：

/**
	 * 大数据量数据分页优化
	 * @param page
	 * @param pageSize
	 * @param lastId 上一页的最大id
	 * @return
	 */
	public List<User> largePageList(int page, int pageSize, int lastId) {
		DB myMongo = MongoManager.getDB("myMongo");
		DBCollection userCollection = myMongo.getCollection("user");
		DBCursor limit = null;
		if (page == 1) {
			limit = userCollection.find()
					.sort(new BasicDBObject("id", 1)).limit(pageSize);
		} else {
			limit = userCollection
					.find(new BasicDBObject("id", new BasicDBObject(
							QueryOperators.GT, lastId)))
					.sort(new BasicDBObject("id", 1)).limit(pageSize);
		}

		List<User> userList = new ArrayList<User>();
		while (limit.hasNext()) {
			User user = new User();
			user.parse(limit.next());
			userList.add(user);
		}
		return userList;
	}
	
	
	public static void main(String[] args) {
		UserDao userDao = new UserDao();
		List<User> largePageList = userDao.largePageList(1,5,0);//第一页
		print(largePageList);
		System.out.println("============");
		List<User> largePageList2 = userDao.largePageList(2,5,5);//第二页   需要记录上一页的最大id
		print(largePageList2);
		System.out.println("============");
		List<User> largePageList3 = userDao.largePageList(3,5,11);//第三页   需要记录上一页的最大id
		print(largePageList3);
	}
	
	public static void print(List<User> largePageList){
		for(User user : largePageList){
			System.out.println(user);
		}
	}

输出结果如下：

id:1,name:jinhui,address:beijing
id:2,name:manman,address:beijing
id:3,name:3,address:3
id:4,name:4,address:4
id:5,name:5,address:5
============
id:6,name:6,address:6
id:7,name:7,address:7
id:8,name:8,address:8
id:9,name:9,address:9
id:11,name:11,address:11
============
id:12,name:12,address:12

我们依靠记录排序，记录下上一页排序列的最大值，来进行下一次分页。从而避免了使用skip操作。