Spring优雅整合Redis缓存 / 憋错料

“小明，多系统的session共享，怎么处理？”“Redis缓存啊！” “小明，我想实现一个简单的消息队列？”“Redis缓存啊！”

“小明，分布式锁这玩意有什么方案？”“Redis缓存啊！” “小明，公司系统响应如蜗牛，咋整？”“Redis缓存啊！”

本着研究的精神，我们来分析下小明的第四个问题。

准备：

Idea2019.03/Gradle6.0.1/Maven3.6.3/JDK11.0.4/Lombok0.28/SpringBoot2.2.4RELEASE/mybatisPlus3.3.0/Soul2.1.2/

Dubbo2.7.5/Druid1.2.21/Zookeeper3.5.5/Mysql8.0.11/Vue2.5/Redis3.2

难度： 新手--战士--老兵--大师

目标：

Spring优雅整合Redis做数据库缓存

步骤：

为了遇见各种问题，同时保持时效性，我尽量使用最新的软件版本。源码地址：https://github.com/xiexiaobiao/vehicle-shop-admin

1 先说结论

Redis缓存不是金弹，若系统DB毫无压力，系统性能瓶颈不在DB上，不建议强加缓存层！

增加业务复杂度：同一缓存必须被全部相关方法所覆盖，如订单缓存，只要涉及到订单数据更新的方法都要进行缓存逻辑处理。

　　　　同时，KV存储时，因各方法返回的类型不同，这样就需要多个缓存池，但各方法后台的数据又存在关联，往往导致一个方法需

　　　　要处理关联的多个缓存，从而形成网状处理逻辑。

　　 2. 存在并发问题：缓存没有锁机制，B线程进行DB更新，同时A线程请求数据，缓存中存在即返回，但B线程还未更新到缓存，导

　　　　致缓存与DB不一致；或者A线程B线程都进行DB更新，但写入缓存的顺序发生颠倒，也会导致缓存与DB不一致，请看官君想想如何解决；

　　 3.内存消耗：小数据量可直接全部进内存，但海量数据不可能全部直接进入Redis，机器吃不消！可考虑只缓存DB数据索引，然后配合

　　　　“布隆过滤器”拦截无效请求，有效请求再去DB查询；

　　 4. 缓存位置：缓存注解的方法，执行时序上应尽量靠近DB，远离前端，如放dao层，请看官君思考下为啥。

适用场景：1.确认DB为系统性能瓶颈，2.数据内容稳定，低频更新，高频查询，如历史订单数据；3.热点数据，如新上市商品；

2 步骤

2.1 原理

这里我说的是注解模式，有四个注解，SpringCache缓存原理即注解+拦截器 org.springframework.cache.interceptor.CacheInterceptor 对方法进行拦截处理：

@Cacheable：可标记在类或方法上。标记在类上则缓存该类所有方法的返回值。请求方法时，先在缓存进行key匹配，存在则直接取缓存数据并返回。主要参数表：

@CacheEvict：从缓存中移除相应数据。主要参数表：

@CachePut：方法支持缓存功能。与@Cacheable不同的是使用@CachePut标注的方法在执行前不会去检查缓存中是否存在之前执行过的结果，

而是每次都会执行该方法，并将执行结果以键值对的形式存入指定的缓存中。主要参数表：

@Caching: 多个Cache注解组合使用,比如新增用户时，同时要删除其他缓存，并更新用户信息缓存，即以上三个注解的集合。

2.2 编码

项目有五个微服务，我仅改造了customer服务模块：

引入依赖，build.gradle文件：

Redis配置项，resources/config/application-dev.yml文件：

文件： com.biao.shop.customer.conf.RedisConf

@Configuration
@EnableCaching
public class RedisConf {

    @Bean
    public RedisCacheManager cacheManager(RedisConnectionFactory redisConnectionFactory){
        return RedisCacheManager.create(redisConnectionFactory);
    }

    @Bean
    public CacheManager cacheManager() {
        // configure and return an implementation of Spring‘s CacheManager SPI
         SimpleCacheManager cacheManager = new SimpleCacheManager();
         cacheManager.setCaches(Arrays.asList(new ConcurrentMapCache("default")));
         return cacheManager;
    }

    @Bean
    public RedisTemplate<String,Object> redisTemplate(RedisConnectionFactory factory){
        RedisTemplate<String,Object> redisTemplate = new RedisTemplate<>();
        redisTemplate.setConnectionFactory(factory);
        // 设置key的序列化器
        redisTemplate.setKeySerializer(new StringRedisSerializer());
        // 设置value的序列化器,使用Jackson 2，将对象序列化为JSON
        Jackson2JsonRedisSerializer jackson2JsonRedisSerializer =
                new Jackson2JsonRedisSerializer(Object.class);
        // json转对象类，不设置,默认的会将json转成hashmap
        ObjectMapper mapper = new ObjectMapper();
        mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
        mapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
        jackson2JsonRedisSerializer.setObjectMapper(mapper);
        return redisTemplate;
    }
}

以上代码解析：1.声明缓存管理器CacheManager，会创建一个切面（aspect）并触发Spring缓存注解的切点，根据类或者方法所使用的注解以及缓存的状态，

这个切面会从缓存中获取数据，将数据添加到缓存之中或者从缓存中移除某个值 2. RedisTemplate即为Redis连接器，实际上即为jedis客户端。

文件： com.biao.shop.customer.impl.ShopClientServiceImpl

@org.springframework.stereotype.Service
@Slf4j
public class ShopClientServiceImpl extends ServiceImpl<ShopClientDao, ShopClientEntity> implements ShopClientService {

    private final Logger logger = LoggerFactory.getLogger(ShopClientServiceImpl.class);

    private ShopClientDao shopClientDao;

    @Autowired
    public ShopClientServiceImpl(ShopClientDao shopClientDao){
        this.shopClientDao = shopClientDao;
    }

    @Override
    public String getMaxClientUuId() {
        return shopClientDao.selectList(new LambdaQueryWrapper<ShopClientEntity>()
                .isNotNull(ShopClientEntity::getClientUuid).orderByDesc(ShopClientEntity::getClientUuid))
                .stream().limit(1).collect(Collectors.toList())
                .get(0).getClientUuid();
    }

    @Override
    @Caching(put = @CachePut(cacheNames = {"shopClient"},key = "#root.args[0].clientUuid"),
            evict = @CacheEvict(cacheNames = {"shopClientPage","shopClientPlateList","shopClientList"},allEntries = true))
    public int createClient(ShopClientEntity clientEntity) {
        clientEntity.setGenerateDate(LocalDateTime.now());
        return shopClientDao.insert(clientEntity);
    }

    /** */
    @Override
    @CacheEvict(cacheNames = {"shopClient","shopClientPage","shopClientPlateList","shopClientList"},allEntries = true)
    public int deleteBatchById(Collection<Integer> ids) {
        logger.info("deleteBatchById 删除Redis缓存");
        return shopClientDao.deleteBatchIds(ids);
    }

    @Override
    @CacheEvict(cacheNames = {"shopClient","shopClientPage","shopClientPlateList","shopClientList"},allEntries = true)
    public int deleteById(int id) {
        logger.info("deleteById 删除Redis缓存");
        return shopClientDao.deleteById(id);
    }

    @Override
    @Caching(evict = {@CacheEvict(cacheNames = "shopClient",key = "#root.args[0]"),
            @CacheEvict(cacheNames = {"shopClientPage","shopClientPlateList","shopClientList"},allEntries = true)})
    public int deleteByUUid(String uuid) {
        logger.info("deleteByUUid 删除Redis缓存");
        QueryWrapper<ShopClientEntity> qw = new QueryWrapper<>();
        qw.eq(true,"uuid",uuid);
        return shopClientDao.delete(qw);
    }

    @Override
    @Caching(put = @CachePut(cacheNames = "shopClient",key = "#root.args[0].clientUuid"),
            evict = @CacheEvict(cacheNames = {"shopClientPage","shopClientPlateList","shopClientList"},allEntries = true))
    public int updateClient(ShopClientEntity clientEntity) {
        logger.info("updateClient 更新Redis缓存");
        clientEntity.setModifyDate(LocalDateTime.now());
        return shopClientDao.updateById(clientEntity);
    }

    @Override
    @CacheEvict(cacheNames = {"shopClient","shopClientPage","shopClientPlateList","shopClientList"},allEntries = true)
    public int addPoint(String uuid,int pointToAdd) {
        ShopClientEntity clientEntity =  this.queryByUuId(uuid);
        log.debug(clientEntity.toString());
        clientEntity.setPoint(Objects.isNull(clientEntity.getPoint()) ? 0 : clientEntity.getPoint() + pointToAdd);
        return shopClientDao.updateById(clientEntity);
    }

    @Override
    @Cacheable(cacheNames = "shopClient",key = "#root.args[0]")
    public ShopClientEntity queryByUuId(String uuid) {
        logger.info("queryByUuId 未使用Redis缓存");
        QueryWrapper<ShopClientEntity> qw = new QueryWrapper<>();
        qw.eq(true,"client_uuid",uuid);
        return shopClientDao.selectOne(qw);
    }

    @Override
    @Cacheable(cacheNames = "shopClientById",key = "#root.args[0]")
    public ShopClientEntity queryById(int id) {
        logger.info("queryById 未使用Redis缓存");
        return shopClientDao.selectById(id);
    }

    @Override
    @Cacheable(cacheNames = "shopClientPage")
    public PageInfo<ShopClientEntity> listClient(Integer current, Integer size, String clientUuid, String name,
                                                 String vehiclePlate, String phone) {
        logger.info("listClient 未使用Redis缓存");
        QueryWrapper<ShopClientEntity> qw = new QueryWrapper<>();
        Map<String,Object> map = new HashMap<>(4);
        map.put("client_uuid",clientUuid);
        map.put("vehicle_plate",vehiclePlate);
        map.put("phone",phone);
        // "name" 模糊匹配
        boolean valid = Objects.isNull(name);
        qw.allEq(true,map,false).like(!valid,"client_name",name);
        PageHelper.startPage(current,size);
        List<ShopClientEntity> clientEntities = shopClientDao.selectList(qw);
        return  PageInfo.of(clientEntities);
    }

    // java Stream
    @Override
    @Cacheable(cacheNames = "shopClientPlateList")
    public List<String> listPlate() {
        logger.info("listPlate 未使用Redis缓存");
        List<ShopClientEntity> clientEntities =
                shopClientDao.selectList(new LambdaQueryWrapper<ShopClientEntity>().isNotNull(ShopClientEntity::getVehiclePlate));
        return clientEntities.stream().map(ShopClientEntity::getVehiclePlate).collect(Collectors.toList());
    }

    @Override
    @Cacheable(cacheNames = "shopClientList",key = "#root.args[0].toString()")
    public List<ShopClientEntity> listByClientDto(ClientQueryDTO clientQueryDTO) {
        logger.info("listByClientDto 未使用Redis缓存");
        QueryWrapper<ShopClientEntity> qw = new QueryWrapper<>();
        boolean phoneFlag = Objects.isNull(clientQueryDTO.getPhone());
        boolean clientNameFlag = Objects.isNull(clientQueryDTO.getClientName());
        boolean vehicleSeriesFlag = Objects.isNull(clientQueryDTO.getVehicleSeries());
        boolean vehiclePlateFlag = Objects.isNull(clientQueryDTO.getVehiclePlate());
        //如有null的条件直接不参与查询
        qw.eq(!phoneFlag,"phone",clientQueryDTO.getPhone())
                .like(!clientNameFlag,"client_name",clientQueryDTO.getClientName())
                .like(!vehicleSeriesFlag,"vehicle_plate",clientQueryDTO.getVehiclePlate())
                .like(!vehiclePlateFlag,"vehicle_series",clientQueryDTO.getVehicleSeries());
        return shopClientDao.selectList(qw);
    }
}