RDB
和 AOF
两种持久化方式,但是普遍还是认为 Redis 的持久化并不是很靠谱。非常重要的数据不要依赖 Redis 来开发,或者最起码不要只在 Redis 中持久化文档参考:http://doc.redisfans.com/
rpush从右往左插入元素,最后插入的元素c在最右边
lpop和rpop分别是从左边和右边取出元素并移除
lrange返回指定范围内的元素
返回集合中元素的个数
zrange按照score从小到大排列
测试环境:阿里云 CentOS 7.6
wget http://download.redis.io/releases/redis-5.0.5.tar.gz
tar xzf redis-5.0.5.tar.gz
cd redis-5.0.5
make
打开src文件夹
./redis-server
./redis-cli shutdown
在redis-5.0.5目录下的redis.conf
在上次集成Druid的基础上集成Redis
https://cloud.tencent.com/developer/article/1512238
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-start-cache</artifactId></dependency>
</dependency>
配置yaml
spring:
datasource:
# 数据源基本配置
username: noneplus
password: MEMMpYHaOUFVuaR37bMbUmGW76WVSLAD7pnFLrbup5H4Q6sZvWMDsYAcnZvAL2hY2Man1rc6SCJMYwrse1xPKw== # 1.配置生成的password
driver-class-name: com.mysql.cj.jdbc.Drive
url: jdbc:mysql://47.103.6.247:3306/user?serverTimezone=UTC
type: com.alibaba.druid.pool.DruidDataSource
# Druid数据源配置
initialSize: 5
minIdle: 5
maxActive: 20
maxWait: 60000
timeBetweenEvictionRunsMillis: 60000
minEvictableIdleTimeMillis: 300000
validationQuery: SELECT 1 FROM DUAL
testWhileIdle: true
testOnBorrow: false
testOnReturn: false
poolPreparedStatements: true
# 配置监控统计拦截的filters,去掉后监控界面sql无法统计,'wall'用于防火墙
filters: stat,wall,log4j,config # 3.添加config
maxPoolPreparedStatementPerConnectionSize: 20
useGlobalDataSourceStat: true
# 2.开启加密,配置公钥
connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=500;config.decrypt=true;config.decrypt.key=MFwwDQYJKoZIhvcNAQEBBQADSwAwSAJBAIIl9Pp9nYiIsVgEgOuNqqyPIU6NsYNSyLX3gxcBhIPRtcL5WqxevYKvsAwaT4WOtww268vHdyP7zWTGhtGxscMCAwEAAQ==
thymeleaf:
cache: false
redis:
host: 47.103.6.247
port: 6379
password: 123456
pagehelper:
helperDialect: mysql
reasonable: true
supportMethodsArguments: true
pageSizeZero: false #pageSize=0
- 测试是否可以正常连接到redis @Autowired StringRedisTemplate stringRedisTemplate; @Test public void testRedis() { stringRedisTemplate.opsForValue().append("ms","hello"); }
package zkrun.top.web.config;
import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.annotation.PropertyAccessor;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.springframework.cache.CacheManager;
import org.springframework.cache.annotation.EnableCaching;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.cache.RedisCacheConfiguration;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer;
import org.springframework.data.redis.serializer.RedisSerializationContext;
import org.springframework.data.redis.serializer.RedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;
import java.time.Duration;
@Configuration
@EnableCaching
public class RedisConfig {
@Bean
public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) {
RedisTemplate<String, Object> redisTemplate = new RedisTemplate<>();
redisTemplate.setConnectionFactory(factory);
// 使用Jackson2JsonRedisSerialize 替换默认序列化
Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class);
ObjectMapper objectMapper = new ObjectMapper();
objectMapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
objectMapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
jackson2JsonRedisSerializer.setObjectMapper(objectMapper);
// 设置value的序列化规则和 key的序列化规则
redisTemplate.setKeySerializer(new StringRedisSerializer());
redisTemplate.setValueSerializer(jackson2JsonRedisSerializer);
redisTemplate.setHashKeySerializer(new StringRedisSerializer());
redisTemplate.setHashValueSerializer(jackson2JsonRedisSerializer);
redisTemplate.afterPropertiesSet();
return redisTemplate;
}
@Bean
public CacheManager cacheManager(RedisConnectionFactory factory) {
RedisSerializer<String> redisSerializer = new StringRedisSerializer();
Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class);
//解决查询缓存转换异常的问题
ObjectMapper om = new ObjectMapper();
om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
jackson2JsonRedisSerializer.setObjectMapper(om);
// 配置序列化(解决乱码的问题),过期时间30秒
RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig()
.entryTtl(Duration.ofSeconds(1800000))
.serializeKeysWith(RedisSerializationContext.SerializationPair.fromSerializer(redisSerializer))
.serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(jackson2JsonRedisSerializer))
.disableCachingNullValues();
RedisCacheManager cacheManager = RedisCacheManager.builder(factory)
.cacheDefaults(config)
.build();
return cacheManager;
}
}
@Autowired
RedisService redisService;
@RequestMapping("/get")
@ResponseBody
public String get(Integer id) {
return redisService.getUserById(id);
}
@RequestMapping("/update")
@ResponseBody
public UserInfo update(UserInfo userInfo)
{
return redisService.updateUser(userInfo);
}
@RequestMapping("/deleteCache")
@ResponseBody
public String delete(Integer id)
{
return redisService.deleteUser(id);
}
package zkrun.top.web.service;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.cache.annotation.CacheEvict;
import org.springframework.cache.annotation.CachePut;
import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;
import zkrun.top.web.bean.UserInfo;
import zkrun.top.web.mapper.UserInfoMapper;
@Service
public class RedisService {
@Autowired
UserInfoMapper userInfoMapper;
/**将方法运行结果进行缓存,当方法被再次调用时,直接返回缓存中的结果。
* 参数:
* value:指定缓存组件的名字
* key:缓存的key。可以使用SpEl表达式
* condition:缓存条件。(为true时缓存),使用EL表达式
* unless:否定缓存。(为true时不缓存)unless在方法执行之后判断,所以unless可以用结 果作为判断条件。
* @param id
* @return
*/
@Cacheable(value = "test", key = "#id")
public String getUserById(Integer id) {
UserInfo userInfo=userInfoMapper.getUserById(id);
return userInfo.toString();
}
//修改了数据库的数据,同时更新缓存。先调用目标方法,然后缓存方法结果。
@CachePut(value = "test",key="#result.id") //只能是result.id
public UserInfo updateUser(UserInfo userInfo) {
userInfoMapper.updateUser(userInfo);
return userInfo;
}
//删除数据之后,清除缓存
@CacheEvict(value = "test", key = "#id")
public String deleteUser(Integer id) {
userInfoMapper.deleteUserById(id);
return "已删除";
}
}
缓存已生成
缓存已更新
数据库已更新
緩存已清空
数据库已删除
https://github.com/HCJ-shadow/SpringBootPlus
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