微服务解决方案 -- Mybatis-Plus + Redis缓存，如何不太优雅的使用Redis缓存

如何不太优雅的使用Redis缓存

我们都知道使用redis来缓存我们的数据集合，如下图所示。

通常自己去缓存数据，这样的优点就是逻辑清晰，而且redis的key和value会比较规范。但是冗余代码会比较多，需要自己进行判断数据是否过期。
为了简化业务代码，现在用注解的方式集成redis二级缓存，但是他的key和value就会比较不符合规范。他的key一共包含5个部分，最重要的就是sql和这个sql的参数。他的value就是这个查询的结果集。

准备工作

引入依赖，mybatis

<dependency><groupId>com.zaxxer</groupId><artifactId>HikariCP</artifactId>
</dependency>
<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-jdbc</artifactId><exclusions><!-- 排除 tomcat-jdbc 以使用 HikariCP --><exclusion><groupId>org.apache.tomcat</groupId><artifactId>tomcat-jdbc</artifactId></exclusion></exclusions>
</dependency><dependency><groupId>com.baomidou</groupId><artifactId>mybatis-plus-boot-starter</artifactId><version>3.0.6</version>
</dependency>
<dependency><groupId>com.baomidou</groupId><artifactId>mybatis-plus-extension</artifactId><version>3.0.6</version>
</dependency>

redis依赖

<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency><groupId>org.apache.commons</groupId><artifactId>commons-pool2</artifactId>
</dependency>

配置文件

spring:datasource:type: com.zaxxer.hikari.HikariDataSourcedriver-class-name: com.mysql.cj.jdbc.Driver# 这里使用的是 ip:3336/db_order 的数据库（一个服务一个数据库）url: jdbc:mysql://localhost:3306/sys-common?useUnicode=true&characterEncoding=utf-8&serverTimezone=Hongkong&useSSL=falseusername: rootpassword: 123456hikari:minimum-idle: 5idle-timeout: 600000maximum-pool-size: 10auto-commit: truepool-name: MyHikariCPmax-lifetime: 1800000connection-timeout: 30000connection-test-query: SELECT 1# redisredis:host: xxx.xxx.xxx.xxxport: 6379lettuce:pool:max-active: 8max-idle: 8max-wait: -1msmin-idle: 0database: 4

配置redisTemplate

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.lettuce.LettuceConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.StringRedisSerializer;/*** ProjectName:     hello-redis-cache* Package:         com.laoshiren.hello.redis.cache.mybatis.configure* ClassName:       RedisConfiguration* Author:          laoshiren* Description:* Date:            2020/9/13 15:49* Version:         1.0*/
@Configuration
public class RedisConfiguration {/*** 设置redisTemplate*/@Bean(name = "redisTemplate")public RedisTemplate<Object, Object> redisTemplate(LettuceConnectionFactory redisConnectionFactory) {RedisTemplate<Object, Object> redisTemplate = new RedisTemplate<>();redisTemplate.setConnectionFactory(redisConnectionFactory);// 使用String 序列化
//        redisTemplate.setDefaultSerializer(new StringRedisSerializer());
//        redisTemplate.setKeySerializer(new StringRedisSerializer());
//        redisTemplate.setValueSerializer(new StringRedisSerializer());redisTemplate.afterPropertiesSet();return redisTemplate;}
}

注意这里我不使用String的序列化方式去序列化Key和Value

实现

实现Cache接口

package com.laoshiren.hello.redis.cache.mybatis.cache;import com.laoshiren.hello.redis.cache.mybatis.configure.ApplicationContextHolder;
import lombok.extern.slf4j.Slf4j;
import org.apache.ibatis.cache.Cache;
import org.springframework.data.redis.core.RedisCallback;
import org.springframework.data.redis.core.RedisTemplate;import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.ReadWriteLock;
import java.util.concurrent.locks.ReentrantReadWriteLock;/*** ProjectName:     hello-redis-cache* Package:         com.laoshiren.hello.redis.cache.mybatis.cache* ClassName:       RedisCache* Author:          laoshiren* Description:* Date:            2020/9/13 15:34* Version:         1.0*/
@Slf4j
public class RedisCache implements Cache {private final ReadWriteLock readWriteLock = new ReentrantReadWriteLock();private final String id; // cache instance idprivate RedisTemplate redisTemplate;private static final long EXPIRE_TIME_IN_MINUTES = 30; // redis过期时间public RedisCache(String id) {if (id == null) {throw new IllegalArgumentException("Cache instances require an ID");}this.id = id;}@Overridepublic String getId() {return id;}/*** Put query result to redis** @param key* @param value*/@Overridepublic void putObject(Object key, Object value) {try {RedisTemplate redisTemplate = getRedisTemplate();redisTemplate.opsForValue().set(key, value, EXPIRE_TIME_IN_MINUTES, TimeUnit.MINUTES);log.debug("Put query result to redis");} catch (Throwable t) {log.error("Redis put failed", t);}}/*** Get cached query result from redis** @param key* @return*/@Overridepublic Object getObject(Object key) {try {RedisTemplate redisTemplate = getRedisTemplate();log.info("Get cached query result from redis");
//            System.out.println("****" + opsForValue.get(key).toString());return redisTemplate.opsForValue().get(key);} catch (Throwable t) {log.error("Redis get failed, fail over to db", t);return null;}}/*** Remove cached query result from redis** @param key* @return*/@Override@SuppressWarnings("unchecked")public Object removeObject(Object key) {try {RedisTemplate redisTemplate = getRedisTemplate();redisTemplate.delete( key.toString());log.debug("Remove cached query result from redis");} catch (Throwable t) {log.error("Redis remove failed", t);}return null;}/*** Clears this cache instance*/@Overridepublic void clear() {RedisTemplate redisTemplate = getRedisTemplate();redisTemplate.execute((RedisCallback) connection -> {connection.flushDb();return null;});log.debug("Clear all the cached query result from redis");}/*** This method is not used** @return*/@Overridepublic int getSize() {return 0;}@Overridepublic ReadWriteLock getReadWriteLock() {return readWriteLock;}private RedisTemplate getRedisTemplate() {if (redisTemplate == null) {redisTemplate = ApplicationContextHolder.getBean("redisTemplate");}return redisTemplate;}
}

给指定的mapper配置缓存

@CacheNamespace(implementation = RedisCache.class)
public interface TbPostMapper extends BaseMapper<TbPost> {}

测试

请求一次数据库，使用Debug模式，它的key是一个CacheKey，无法使用使用StringRedisSerializer去序列化，所以redisTemplate 得使用默认的序列化，即 JdkSerializationRedisSerializer

打开RDM，看一下4号库。

发现key和value就不是很美观，不过不影响使用，当然您可以使用StringRedisSerializer去实现，只不过我在尝试的过程中获取sql和参数的时候，会出现一点问题。希望有大佬可以指出。

带参数的sql

特别注意! 在分页缓存的时候，Page对象的total必须自己手动查询一次，不然返回给前端的对象里第一次还有总页数，第二次由于走了缓存就不带这个total，所以必须手动查询一次。

@GetMapping("page/{pageNo}/{pageSize}")
public ResponseResult<IPage<Area>> page(@PathVariable(name = "pageNo")Integer pageNo,@PathVariable(name = "pageSize") Integer pageSize,HttpServletRequest request){IPage<Area> wherePage = new Page<>(pageNo, pageSize);String word = request.getParameter("wd");LambdaQueryWrapper<Area> queryWrapper = new LambdaQueryWrapper<>();if (StringUtils.isNotBlank(word)) {queryWrapper.like(Area::getAreaName,word);}int count = areaService.count(queryWrapper);IPage<Area> page = areaService.page(wherePage,queryWrapper);page.setTotal((long)count);return new ResponseResult<>(CodeStatus.OK,"操作成功",page);
}

后续我也会继续更新这篇博客。好了，最后还是借用大佬的一句话：“不经一番寒彻骨，怎知梅花扑鼻香”。