Redis 实现排行榜

Controller 层

@RestController
public class RankingController {

    @Autowired
    private RangingService rankingService;

    @RequestMapping("/addScore")
    public String addRank(String uid, Integer score) {
        rankingService.rankAdd(uid, score);
        return "success";
    }

    @RequestMapping("/increScore")
    public String increScore(String uid, Integer score) {
        rankingService.increSocre(uid, score);
        return "success";
    }

    @RequestMapping("/rank")
    public Map<String, Long> rank(String uid) {
        Map<String, Long> map = new HashMap<>();
        map.put(uid, rankingService.rankNum(uid));
        return map;
    }

    @RequestMapping("/score")
    public Long rankNum(String uid) {
        return rankingService.score(uid);
    }

    @RequestMapping("/scoreByRange")
    public Set<ZSetOperations.TypedTuple<Object>> scoreByRange(Integer start, Integer end) {
        return rankingService.rankWithScore(start,end);
    }

    @RequestMapping("/sale/increScore")
    public String increSaleScore(String uid, Integer score) {
        rankingService.increSaleSocre(uid, score);
        return "success";
    }

    @RequestMapping("/sale/userScore")
    public Map<String,Object> userScore(String uid,String name) {
        return rankingService.userRank(uid,name);
    }

    @RequestMapping("/sale/top")
    public List<Map<String,Object>> reverseZRankWithRank(long start,long end) {
        return rankingService.reverseZRankWithRank(start,end);
    }

    @RequestMapping("/sale/scoreByRange")
    public List<Map<String,Object>> saleScoreByRange(Integer start, Integer end) {
        return rankingService.saleRankWithScore(start,end);
    }

}

RankingController

Service 层

@Service
public class RangingService implements InitializingBean {


    private static final String RANKGNAME = "user_score";

    private static final String SALESCORE = "sale_score_rank:";

    @Autowired
    private RedisService redisService;

    @Autowired
    private UserMapper userMapper;

    @Autowired
    private ScoreFlowMapper scoreFlowMapper;

    @Autowired
    private UserScoreMapper userScoreMapper;


    public void rankAdd(String uid, Integer score) {
        redisService.zAdd(RANKGNAME, uid, score);
    }

    public void increSocre(String uid, Integer score) {

        redisService.incrementScore(RANKGNAME, uid, score);
    }

    public Long rankNum(String uid) {
        return redisService.zRank(RANKGNAME, uid);
    }

    public Long score(String uid) {
        Long score = redisService.zSetScore(RANKGNAME, uid).longValue();
        return score;
    }

    public Set<ZSetOperations.TypedTuple<Object>> rankWithScore(Integer start, Integer end) {
        return redisService.zRankWithScore(RANKGNAME, start, end);
    }


    public void rankSaleAdd() {
        UserScoreExample example = new UserScoreExample();
        example.setOrderByClause("id desc");
        List<UserScore> userScores = userScoreMapper.selectByExample(example);
        userScores.forEach(userScore -> {
            String key = userScore.getUserId() + ":" + userScore.getName();
            redisService.zAdd(SALESCORE, key, userScore.getUserScore());
        });
    }


    /**
     * 添加用户积分
     *
     * @param uid
     * @param score
     */
    public void increSaleSocre(String uid, Integer score) {
        User user = userMapper.find(uid);
        if (user == null) {
            return;
        }
        int uidInt = Integer.parseInt(uid);
        long socreLong = Long.parseLong(score + "");
        String name = user.getUserName();
        String key = uid + ":" + name;
        scoreFlowMapper.insertSelective(new ScoreFlow(socreLong, uidInt, name));
        userScoreMapper.insertSelective(new UserScore(uidInt, socreLong, name));
        redisService.incrementScore(SALESCORE, key, score);
    }


    public Map<String, Object> userRank(String uid, String name) {
        Map<String, Object> retMap = new LinkedHashMap<>();
        String key = uid + ":" + name;
        Integer rank = redisService.zRank(SALESCORE, key).intValue();
        Long score = redisService.zSetScore(SALESCORE, key).longValue();
        retMap.put("userId", uid);
        retMap.put("score", score);
        retMap.put("rank", rank);
        return retMap;
    }


    public List<Map<String, Object>> reverseZRankWithRank(long start, long end) {
        Set<ZSetOperations.TypedTuple<Object>> setObj = redisService.reverseZRankWithRank(SALESCORE, start, end);
        List<Map<String, Object>> mapList = setObj.stream().map(objectTypedTuple -> {
            Map<String, Object> map = new LinkedHashMap<>();
            map.put("userId", objectTypedTuple.getValue().toString().split(":")[0]);
            map.put("userName", objectTypedTuple.getValue().toString().split(":")[1]);
            map.put("score", objectTypedTuple.getScore());
            return map;
        }).collect(Collectors.toList());
        return mapList;
    }

    public List<Map<String, Object>> saleRankWithScore(Integer start, Integer end) {
        Set<ZSetOperations.TypedTuple<Object>> setObj = redisService.reverseZRankWithScore(SALESCORE, start, end);
        List<Map<String, Object>> mapList = setObj.stream().map(objectTypedTuple -> {
            Map<String, Object> map = new LinkedHashMap<>();
            map.put("userId", objectTypedTuple.getValue().toString().split(":")[0]);
            map.put("userName", objectTypedTuple.getValue().toString().split(":")[1]);
            map.put("score", objectTypedTuple.getScore());
            return map;
        }).collect(Collectors.toList());
        return mapList;
    }

//    @Override
//    public void run(ApplicationArguments args) throws Exception {
//        System.out.println("======enter run bean=======");
//        Thread.sleep(100000);
//        this.rankSaleAdd();
//    }


    @Override
    public void afterPropertiesSet() throws Exception {
        System.out.println("======enter init bean=======");
        this.rankSaleAdd();
    }
}

RangingService 实现业务

工具类

@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 get(final String key) {
        Object result = null;
        ValueOperations<Serializable, Object> 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;
    }
}

工具类

虽然 Redis 帮助我们快速存读数据，但这些数据还是得落到数据库中进行保存，数据库表设计过程中几个关键要点：

1、表设计过程中应该注意：数据类型

更小的通常更好，控制字节长度。
使用合适的数据类型。如 tinyint 只占8个位，char(1024) 与 varchar(1024) 的对比——char 用于类似定长数据存储比 varchar 节省空间，如：uuid（32），可以用 char(32)。
尽量避免NULL，建议使用 NOT NULL，DEFAULT '' 创建字段。NULL 的列会让索引统计和值比较都更复杂。可为 NULL 的列会占据更多的磁盘空间，在 Mysql 中也需要更多复杂的处理程序。

2、表设计过程中应该注意：索引

选择唯一性索引。唯一性索引的值是唯一的，可以更快速的通过该索引来确定某条记录，保证物理上面唯一。
为经常需要排序、分组和联合操作的字段建立索引。经常需要 ORDER BY、GROUP BY、DISTINCT 和 UNION 等操作的字段，排序操作会浪费很多时间。
常作为查询条件的字段建立索引。如果某个字段经常用来做查询条件，那么该字段的查询速度会影响整个表的查询速度。
数据少的地方不必建立索引。

3、表使用过程中应该注意：sql 优化

能够用 BETWEEN 的就不要用 IN
能够用 DISTINCT 的就不用 GROUP BY
避免数据类型强转
学会采用 explain 查看执行计划（注意：扫描行数会影响CPU运行，占用大量内存）

有些缓存数据并不是用户访问触发的，而是在项目启动时就加载到缓存中的，Spring Boot 实现初始化加载配置（实现缓存预热），主要有两种方法：

采用实现 ApplicationRunner 接口。该方法仅在 SpringApplication.run(…) 完成之前调用
采用实现 InitializingBean 接口。InitializingBean 接口为 bean 提供了初始化方法的方式，它只包括 afterPropertiesSet() 方法。在 Spring 初始化 bean 的时候，如果 bean 实现了 InitializingBean 接口，在对象的所有属性被初始化后之后才会调用 afterPropertiesSet() 方法

两种方式的区别在于：实现 ApplicationRunner 不会影响项目启动，而实现 InitializingBean 则项目必须等待方法走完才会真正启动。

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原文地址：https://www.cnblogs.com/jwen1994/p/12248885.html