1、引入pom依赖
<!-- redis 缓存操作 -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
2、增加配置类 RedisConfig
package com.ruoyi.framework.config;
import org.springframework.cache.annotation.CachingConfigurerSupport;
import org.springframework.cache.annotation.EnableCaching;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.StringRedisSerializer;
import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.annotation.PropertyAccessor;
import com.fasterxml.jackson.databind.ObjectMapper;
/**
* redis配置
*
* @author ruoyi
*/
@Configuration
@EnableCaching
public class RedisConfig extends CachingConfigurerSupport
{
@Bean
@SuppressWarnings(value = { "unchecked", "rawtypes" })
public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory connectionFactory)
{
RedisTemplate<Object, Object> template = new RedisTemplate<>();
template.setConnectionFactory(connectionFactory);
FastJson2JsonRedisSerializer serializer = new FastJson2JsonRedisSerializer(Object.class);
ObjectMapper mapper = new ObjectMapper();
mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
mapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
serializer.setObjectMapper(mapper);
template.setValueSerializer(serializer);
// 使用StringRedisSerializer来序列化和反序列化redis的key值
template.setKeySerializer(new StringRedisSerializer());
template.afterPropertiesSet();
return template;
}
}
3、自定义 redis 工具类
package com.ruoyi.common.core.redis;
import java.util.Collection;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.TimeUnit;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.BoundSetOperations;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.stereotype.Component;
/**
* spring redis 工具类
*
* @author ruoyi
**/
@SuppressWarnings(value = { "unchecked", "rawtypes" })
@Component
public class RedisCache
{
@Autowired
public RedisTemplate redisTemplate;
/**
* 缓存基本的对象,Integer、String、实体类等
*
* @param key 缓存的键值
* @param value 缓存的值
*/
public <T> void setCacheObject(final String key, final T value)
{
redisTemplate.opsForValue().set(key, value);
}
/**
* 缓存基本的对象,Integer、String、实体类等
*
* @param key 缓存的键值
* @param value 缓存的值
* @param timeout 时间
* @param timeUnit 时间颗粒度
*/
public <T> void setCacheObject(final String key, final T value, final Integer timeout, final TimeUnit timeUnit)
{
redisTemplate.opsForValue().set(key, value, timeout, timeUnit);
}
/**
* 设置有效时间
*
* @param key Redis键
* @param timeout 超时时间
* @return true=设置成功;false=设置失败
*/
public boolean expire(final String key, final long timeout)
{
return expire(key, timeout, TimeUnit.SECONDS);
}
/**
* 设置有效时间
*
* @param key Redis键
* @param timeout 超时时间
* @param unit 时间单位
* @return true=设置成功;false=设置失败
*/
public boolean expire(final String key, final long timeout, final TimeUnit unit)
{
return redisTemplate.expire(key, timeout, unit);
}
/**
* 获得缓存的基本对象。
*
* @param key 缓存键值
* @return 缓存键值对应的数据
*/
public <T> T getCacheObject(final String key)
{
ValueOperations<String, T> operation = redisTemplate.opsForValue();
return operation.get(key);
}
/**
* 删除单个对象
*
* @param key
*/
public boolean deleteObject(final String key)
{
return redisTemplate.delete(key);
}
/**
* 删除集合对象
*
* @param collection 多个对象
* @return
*/
public long deleteObject(final Collection collection)
{
return redisTemplate.delete(collection);
}
/**
* 缓存List数据
*
* @param key 缓存的键值
* @param dataList 待缓存的List数据
* @return 缓存的对象
*/
public <T> long setCacheList(final String key, final List<T> dataList)
{
Long count = redisTemplate.opsForList().rightPushAll(key, dataList);
return count == null ? 0 : count;
}
/**
* 获得缓存的list对象
*
* @param key 缓存的键值
* @return 缓存键值对应的数据
*/
public <T> List<T> getCacheList(final String key)
{
return redisTemplate.opsForList().range(key, 0, -1);
}
/**
* 缓存Set
*
* @param key 缓存键值
* @param dataSet 缓存的数据
* @return 缓存数据的对象
*/
public <T> BoundSetOperations<String, T> setCacheSet(final String key, final Set<T> dataSet)
{
BoundSetOperations<String, T> setOperation = redisTemplate.boundSetOps(key);
Iterator<T> it = dataSet.iterator();
while (it.hasNext())
{
setOperation.add(it.next());
}
return setOperation;
}
/**
* 获得缓存的set
*
* @param key
* @return
*/
public <T> Set<T> getCacheSet(final String key)
{
return redisTemplate.opsForSet().members(key);
}
/**
* 缓存Map
*
* @param key
* @param dataMap
*/
public <T> void setCacheMap(final String key, final Map<String, T> dataMap)
{
if (dataMap != null) {
redisTemplate.opsForHash().putAll(key, dataMap);
}
}
/**
* 获得缓存的Map
*
* @param key
* @return
*/
public <T> Map<String, T> getCacheMap(final String key)
{
return redisTemplate.opsForHash().entries(key);
}
/**
* 往Hash中存入数据
*
* @param key Redis键
* @param hKey Hash键
* @param value 值
*/
public <T> void setCacheMapValue(final String key, final String hKey, final T value)
{
redisTemplate.opsForHash().put(key, hKey, value);
}
/**
* 获取Hash中的数据
*
* @param key Redis键
* @param hKey Hash键
* @return Hash中的对象
*/
public <T> T getCacheMapValue(final String key, final String hKey)
{
HashOperations<String, String, T> opsForHash = redisTemplate.opsForHash();
return opsForHash.get(key, hKey);
}
/**
* 获取多个Hash中的数据
*
* @param key Redis键
* @param hKeys Hash键集合
* @return Hash对象集合
*/
public <T> List<T> getMultiCacheMapValue(final String key, final Collection<Object> hKeys)
{
return redisTemplate.opsForHash().multiGet(key, hKeys);
}
/**
* 获得缓存的基本对象列表
*
* @param pattern 字符串前缀
* @return 对象列表
*/
public Collection<String> keys(final String pattern)
{
return redisTemplate.keys(pattern);
}
}
4、yml文件配置
spring:
# redis 配置
redis:
# 地址
host: 33.1.123.32
# 端口,默认为6379
port: 6379
# 密码
password:
# 连接超时时间
timeout: 10s
lettuce:
pool:
# 连接池中的最小空闲连接
min-idle: 0
# 连接池中的最大空闲连接
max-idle: 8
# 连接池的最大数据库连接数
max-active: 8
# #连接池最大阻塞等待时间(使用负值表示没有限制)
max-wait: -1ms