Jingdong Jingdou lottery solution

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I. Business scenario analysis of Jingdong Jingdou Lottery

1. Click Jingdong on the home page of jingdong app to enter the Smoking Jingdou page
2. Each award is differentThe probability ofOpportunity. Beijing bean has a 1/4 chance
3. canrepeatSweepstakes, prize pool probabilities remain the same

Two, jingdong Jingdou lottery technical scheme

Beijing beans lottery is generally used redis set set to operate, then why is the set set applicable to the lottery?

1. The set is characterized byElements do not repeat(1 jingdou 5 Jingdou 10 Jingdou thank you for participating)
2. Set set supportRandom reads

The specific technical scheme is to use the set set srandmember command to achieve a random return set element

Three, case combat: SpringBoot+Redis to achieve jingdong Jingdou lottery

Step 1: Initialize the prize

Since the set set is not duplicated, a sequence number is set for each prize when the prize is initialized.

    /** * Flush the data to the Redis cache first. * /
    @PostConstruct
    public void init(a){
        boolean bo=this.redisTemplate.hasKey(Constants.PRIZE_KEY);
        if(! bo){// Initialize the prize with a probability
            List<String> crowds=this.prize();
            crowds.forEach(t->this.redisTemplate.opsForSet().add(Constants.PRIZE_KEY,t)); }}/** * Initializes the prize with a probability */
    public List<String> prize(a) {
        List<String> list=new ArrayList<>();
        //10 Peking beans, probability 10%
        for (int i = 0; i < 10; i++) {
            list.add("10 -"+i);
        }
        //5 Peking beans, 20% chance
        for (int i = 0; i < 20; i++) {
            list.add("5 -"+i);
        }
        //1 Peking bean, probability 60%
        for (int i = 0; i < 60; i++) {
            list.add("1 -"+i);
        }
        //0 Beijing beans, probability 10%
        for (int i = 0; i < 10; i++) {
            list.add("0"+i);
        }
        return list;
    }
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Step 2: Raffle

    @GetMapping(value = "/prize")
    public String prize(a) {
        String result="";
        try {
            // Select 1 time at random.
            String object = (String)this.redisTemplate.opsForSet().randomMember(Constants.PRIZE_KEY);
            if(! StringUtils.isEmpty(object)){// Intercept the serial number such as 10-1
                int temp=object.indexOf(The '-');
                int no=Integer.valueOf(object.substring(0,temp));
                switch (no){
                    case 0:
                        result="What a pity!";
                        break;
                    case 1:
                        result="Get a King bean";
                        break;
                    case 5:
                        result="Obtain 5 Peking Beans.";
                        break;
                    case 10:
                        result="Earn 10 Peking Beans.";
                        break;
                    default:
                        result="What a pity!";
                }
            }
            log.info("Query result: {}", object);
        } catch (Exception ex) {
            log.error("exception:", ex);
        }
        return result;
    }
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Redis distributed cache family

• Redis Distributed Cache (1) – Redis Installation (Linux and Docker)
• Redis Distributed cache (ii) – RDB and AOF
• SpringBoot integrates Mybatis-Plus,Redis and Swagger
• Redis distributed cache (4) – SpringCache integrates redis
• Redis Distributed Cache (5) — Common command (String)
• Redis distributed cache (vi) – article read volume PV solution
• Redis Distributed cache (7) – distributed global ID solution
• Redis Distributed Cache (8) — Highly Concurrent atomic Operations (Redis+Lua)
• Redis Distributed cache (NINE) – a hacker anti-brush attack solution
• Redis Distributed Cache (10) common Commands (Hash)
• Redis Distributed Cache (11) stores Java Bean object business profile one by one
• Redis distributed Cache (twelve) — short link solution
• Redis Distributed Cache (13) — JD Shopping cart solution
• Redis distributed cache (14) – distributed session inconsistency solution
• Redis Distributed Cache (15) – a highly available user registration solution
• Redis distributed Cache (16) – user microblogging solution
• Redis Distributed cache (17)
• Redis Distributed Cache (18) – one – blacklist verifier solution
• The article continues to be updated…