微信红包实现原理

接口开发说明

发红包功能接口开发

• 新增一条红包记录
• 往 mysql 里面添加一条红包记录
• 往 redis 里面添加一条红包数量记录
• 往 redis 里面添加一条红包金额记录

抢红包功能接口开发

• 在抢红包这里并不能保证用户已经能领到这个红包
• 抢红包只是做了一个判断，判断当前是否还有红包
• 有红包则返回可以领
• 没红包则返回不可以领

拆红包功能接口开发

• 拆红包才是用户能领到红包
• 这时候要先减 redis 里面的金额和红包数量 decr  decreby
• 减完金额再入库

微信红包设计算法分析

玩法：微信金额是拆的时候实时算出来，不是预先分配的，采用的是纯内存计算，不需要预算空间存储

分配：

• 发100块钱，总共10个红包，那么平均值是10块钱一个，那么发出来的红包的额度在0.01元～20元之间波动
• 当前面4个红包总共被领了30块钱时，剩下70块钱，总共6个红包，那么这7个红包的额度在：0.01～（70➗6✖️2）=23.33之间波动
• 这样算下去，可能会超过最开始的全部金额，因此到了最后面如果不够这么算，那么会采取如下算法：保证剩余用户能拿到最低1分钱即可

存储：数据库会累加已经领取的个数与金额，插入一条领取记录。入账则是后台异步操作

转账：通过财付通往红包所得者账户转账，过程通过是异步操作

数据表设计

CREATE TABLE `red_packet_info` (
    `id` int(11) NOT NULL AUTO_INCREMENT, 
    `red_packet_id` bigint(11) NOT NULL DEFAULT  0 COMMENT '红包id，采用timestamp+5位随机数', 
    `total_amount` int(11) NOT NULL DEFAULT 0 COMMENT '红包总金额，单位分',
    `total_packet` int(11) NOT NULL DEFAULT 0 COMMENT '红包总个数',
    `remaining_amount` int(11) NOT NULL DEFAULT 0 COMMENT '剩余红包金额，单位分',
    `remaining_packet` int(11) NOT NULL DEFAULT 0 COMMENT '剩余红包个数',
    `uid` int(20) NOT NULL DEFAULT 0 COMMENT '新建红包用户的用户标识',
    `create_time` timestamp  COMMENT '创建时间',
    `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
    PRIMARY KEY (`id`)
  ) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='红包信息表，新建一个红包插入一条记录';


CREATE TABLE `red_packet_record` (
    `id` int(11) NOT NULL AUTO_INCREMENT, 
    `amount` int(11) NOT NULL DEFAULT '0' COMMENT '抢到红包的金额',
    `nick_name` varchar(32) NOT NULL DEFAULT '0' COMMENT '抢到红包的用户的用户名',
    `img_url` varchar(255) NOT NULL DEFAULT '0' COMMENT '抢到红包的用户的头像',
    `uid` int(20) NOT NULL DEFAULT '0' COMMENT '抢到红包用户的用户标识',
    `red_packet_id` bigint(11) NOT NULL DEFAULT '0' COMMENT '红包id，采用timestamp+5位随机数', 
    `create_time` timestamp  COMMENT '创建时间',
    `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
    PRIMARY KEY (`id`)
  ) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='抢红包记录表，抢一个红包插入一条记录';

代码实现

@RestController
public class RedPacketController {


    @Autowired
    private RedisService redisService;

    @Autowired
    private RedPacketInfoMapper redPacketInfoMapper;

    @Autowired
    private RedPacketRecordMapper redPacketRecordMapper;

    private static final String TOTAL_NUM = "_totalNum";
    private static final String TOTAL_AMOUNT = "_totalAmount";

    /***
     * 发红包
     * @param uid
     * @param totalNum
     * @return
     */
    @ResponseBody
    @RequestMapping("/addPacket")
    public String saveRedPacket(Integer uid, Integer totalNum, Integer totalAmount) {
        RedPacketInfo record = new RedPacketInfo();
        record.setUid(uid);
        record.setTotalAmount(totalAmount);
        record.setTotalPacket(totalNum);
        record.setCreateTime(new Date());
        record.setRemainingAmount(totalAmount);
        record.setRemainingPacket(totalNum);
        long redPacketId = System.currentTimeMillis();   //此时无法保证红包id唯一，最好是用雪花算法进行生成分布式系统唯一键
        record.setRedPacketId(redPacketId);
        redPacketInfoMapper.insert(record);
        redisService.set(redPacketId + "_totalNum", totalNum + "");
        redisService.set(redPacketId + "_totalAmount", totalAmount + "");
        return "success";
    }


    /**
     * 抢红包
     *
     * @param redPacketId
     * @return
     */
    @ResponseBody
    @RequestMapping("/getPacket")
    public Integer getRedPacket(long redPacketId) {
        String redPacketName = redPacketId + TOTAL_NUM;
        String num = (String) redisService.get(redPacketName);
        if (StringUtils.isNotBlank(num)) {
            return Integer.parseInt(num);
        }
        return 0;
    }


    /**
     * 拆红包
     *
     * @param redPacketId
     * @return
     */
    @ResponseBody
    @RequestMapping("/getRedPacketMoney")
    public String getRedPacketMoney(int uid, long redPacketId) {
        Integer randomAmount = 0;
        String redPacketName = redPacketId + TOTAL_NUM;
        String totalAmountName = redPacketId + TOTAL_AMOUNT;
        String num = (String) redisService.get(redPacketName);
        if (StringUtils.isBlank(num) || Integer.parseInt(num) == 0) {
            return "抱歉！红包已经抢完了";
        }
        String totalAmount = (String) redisService.get(totalAmountName);
        if (StringUtils.isNotBlank(totalAmount)) {
            Integer totalAmountInt = Integer.parseInt(totalAmount);
            Integer totalNumInt = Integer.parseInt(num);
            Integer maxMoney = totalAmountInt / totalNumInt * 2;
            Random random = new Random();
            randomAmount = random.nextInt(maxMoney);
        }
        //课堂作业：lua脚本将这两个命令一起请求
        redisService.decr(redPacketName, 1);
        redisService.decr(totalAmountName,randomAmount);  //redis decreby功能
        updateRacketInDB(uid, redPacketId,randomAmount);
        return randomAmount + "";
    }

    public void updateRacketInDB(int uid, long redPacketId, int amount) {
        RedPacketRecord redPacketRecord = new RedPacketRecord();
        redPacketRecord.setUid(uid);
        redPacketRecord.setRedPacketId(redPacketId);
        redPacketRecord.setAmount(1111);
        redPacketRecord.setCreateTime(new Date());
        redPacketRecordMapper.insertSelective(redPacketRecord);
        //这里应该查出RedPacketInfo的数量，将总数量和总金额减去
    }


}

@Service
public class RedisService {

    @Autowired
    private RedisTemplate redisTemplate;

    private static double size = Math.pow(2, 32);


    /**
     * 写入缓存
     *
     * @param key
     * @param offset   位 8Bit=1Byte
     * @return
     */
    public boolean setBit(String key, long offset, boolean isShow) {
        boolean result = false;
        try {
            ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
            operations.setBit(key, offset, isShow);
            result = true;
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }

    /**
     * 写入缓存
     *
     * @param key
     * @param offset
     * @return
     */
    public boolean getBit(String key, long offset) {
        boolean result = false;
        try {
            ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
            result = operations.getBit(key, offset);
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }


    /**
     * 写入缓存
     *
     * @param key
     * @param value
     * @return
     */
    public boolean set(final String key, Object value) {
        boolean result = false;
        try {
            ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
            operations.set(key, value);
            result = true;
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }


    /**
     * 写入缓存
     *
     * @param key
     * @return
     */
    public Object get(final String key) {
        boolean result = false;
        try {
            ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
            return operations.get(key);
        } catch (Exception e) {
            e.printStackTrace();
            return null;
        }
    }


    /**
     * 写入缓存
     *
     * @param key
     * @param value
     * @return
     */
    public boolean decr(final String key, int value) {
        boolean result = false;
        try {
            ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
            operations.increment(key,-value);
            result = true;
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }

    /**
     * 写入缓存设置时效时间
     *
     * @param key
     * @param value
     * @return
     */
    public boolean set(final String key, Object value, Long expireTime) {
        boolean result = false;
        try {
            ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
            operations.set(key, value);
            redisTemplate.expire(key, expireTime, TimeUnit.SECONDS);
            result = true;
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }

    /**
     * 批量删除对应的value
     *
     * @param keys
     */
    public void remove(final String... keys) {
        for (String key : keys) {
            remove(key);
        }
    }


    /**
     * 删除对应的value
     *
     * @param key
     */
    public void remove(final String key) {
        if (exists(key)) {
            redisTemplate.delete(key);
        }
    }

    /**
     * 判断缓存中是否有对应的value
     *
     * @param key
     * @return
     */
    public boolean exists(final String key) {
        return redisTemplate.hasKey(key);
    }

    /**
     * 读取缓存
     *
     * @param key
     * @return
     */
    public Object genValue(final String key) {
        Object result = null;
        ValueOperations<String, String> operations = redisTemplate.opsForValue();
        result = operations.get(key);
        return result;
    }

    /**
     * 哈希 添加
     *
     * @param key
     * @param hashKey
     * @param value
     */
    public void hmSet(String key, Object hashKey, Object value) {
        HashOperations<String, Object, Object> hash = redisTemplate.opsForHash();
        hash.put(key, hashKey, value);
    }

    /**
     * 哈希获取数据
     *
     * @param key
     * @param hashKey
     * @return
     */
    public Object hmGet(String key, Object hashKey) {
        HashOperations<String, Object, Object> hash = redisTemplate.opsForHash();
        return hash.get(key, hashKey);
    }

    /**
     * 列表添加
     *
     * @param k
     * @param v
     */
    public void lPush(String k, Object v) {
        ListOperations<String, Object> list = redisTemplate.opsForList();
        list.rightPush(k, v);
    }

    /**
     * 列表获取
     *
     * @param k
     * @param l
     * @param l1
     * @return
     */
    public List<Object> lRange(String k, long l, long l1) {
        ListOperations<String, Object> list = redisTemplate.opsForList();
        return list.range(k, l, l1);
    }

    /**
     * 集合添加
     *
     * @param key
     * @param value
     */
    public void add(String key, Object value) {
        SetOperations<String, Object> set = redisTemplate.opsForSet();
        set.add(key, value);
    }

    /**
     * 集合获取
     *
     * @param key
     * @return
     */
    public Set<Object> setMembers(String key) {
        SetOperations<String, Object> set = redisTemplate.opsForSet();
        return set.members(key);
    }

    /**
     * 有序集合添加
     *
     * @param key
     * @param value
     * @param scoure
     */
    public void zAdd(String key, Object value, double scoure) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        zset.add(key, value, scoure);
    }

    /**
     * 有序集合获取
     *
     * @param key
     * @param scoure
     * @param scoure1
     * @return
     */
    public Set<Object> rangeByScore(String key, double scoure, double scoure1) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        redisTemplate.opsForValue();
        return zset.rangeByScore(key, scoure, scoure1);
    }


    //第一次加载的时候将数据加载到redis中
    public void saveDataToRedis(String name) {
        double index = Math.abs(name.hashCode() % size);
        long indexLong = new Double(index).longValue();
        boolean availableUsers = setBit("availableUsers", indexLong, true);
    }

    //第一次加载的时候将数据加载到redis中
    public boolean getDataToRedis(String name) {

        double index = Math.abs(name.hashCode() % size);
        long indexLong = new Double(index).longValue();
        return getBit("availableUsers", indexLong);
    }

    /**
     * 有序集合获取排名
     *
     * @param key 集合名称
     * @param value 值
     */
    public Long zRank(String key, Object value) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        return zset.rank(key,value);
    }


    /**
     * 有序集合获取排名
     *
     * @param key
     */
    public Set<ZSetOperations.TypedTuple<Object>> zRankWithScore(String key, long start,long end) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        Set<ZSetOperations.TypedTuple<Object>> ret = zset.rangeWithScores(key,start,end);
        return ret;
    }

    /**
     * 有序集合添加
     *
     * @param key
     * @param value
     */
    public Double zSetScore(String key, Object value) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        return zset.score(key,value);
    }


    /**
     * 有序集合添加分数
     *
     * @param key
     * @param value
     * @param scoure
     */
    public void incrementScore(String key, Object value, double scoure) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        zset.incrementScore(key, value, scoure);
    }


    /**
     * 有序集合获取排名
     *
     * @param key
     */
    public Set<ZSetOperations.TypedTuple<Object>> reverseZRankWithScore(String key, long start,long end) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        Set<ZSetOperations.TypedTuple<Object>> ret = zset.reverseRangeByScoreWithScores(key,start,end);
        return ret;
    }

    /**
     * 有序集合获取排名
     *
     * @param key
     */
    public Set<ZSetOperations.TypedTuple<Object>> reverseZRankWithRank(String key, long start, long end) {
        ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
        Set<ZSetOperations.TypedTuple<Object>> ret = zset.reverseRangeWithScores(key, start, end);
        return ret;
    }

}

 

抢红包功能扩展设计

• 将红包 ID 的请求放入请求队列中，如果发现超过红包的个数，直接返回
• 类推出 token 令牌和秒杀设计原理

注意点

• 抢到红包不代表能拆成功
• 2014 年的红包一点开就知道金额，分两次操作，先抢到金额，然后再转账。2015 年后的红包的拆和抢是分离的，需要点两次，因此会出现抢到红包了，但点开后告知红包已经被领完的状况。进入到第一个页面不代表抢到，只表示当时红包还有。