SpringBoot整合Redis
依赖引入
<!-- 阿里JSON解析器 -->
<dependency>
<groupId>com.alibaba.fastjson2</groupId>
<artifactId>fastjson2</artifactId>
</dependency>
<!-- redis 缓存操作 -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<!-- pool 对象池 -->
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-pool2</artifactId>
</dependency>
yaml配置
# Spring配置
spring:
# redis 配置
redis:
# 地址
host: 127.0.0.1
# 端口,默认为6379
port: 6379
# 数据库索引
database: 0
# 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
使用FastJson序列化
参考 :Fastjson2 官方提供的
/**
* Redis使用FastJson序列化
*
*/
public class FastJson2JsonRedisSerializer<T> implements RedisSerializer<T>
{
public static final Charset DEFAULT_CHARSET = StandardCharsets.UTF_8;
private Class<T> clazz;
public FastJson2JsonRedisSerializer(Class<T> clazz)
{
super();
this.clazz = clazz;
}
@Override
public byte[] serialize(T t) throws SerializationException
{
if (t == null)
{
return new byte[0];
}
return JSON.toJSONString(t, JSONWriter.Feature.WriteClassName).getBytes(DEFAULT_CHARSET);
}
@Override
public T deserialize(byte[] bytes) throws SerializationException
{
if (bytes == null || bytes.length <= 0)
{
return null;
}
String str = new String(bytes, DEFAULT_CHARSET);
return JSON.parseObject(str, clazz, JSONReader.Feature.SupportAutoType);
}
}
RedisConfig
/**
* redis配置
*
*/
@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);
// 使用StringRedisSerializer来序列化和反序列化redis的key值
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(serializer);
// Hash的key也采用StringRedisSerializer的序列化方式
template.setHashKeySerializer(new StringRedisSerializer());
template.setHashValueSerializer(serializer);
template.afterPropertiesSet();
return template;
}
}
Redis工具类
/**
* spring redis 工具类
*
**/
@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);
}
/**
* 删除Hash中的数据
*
* @param key
* @param hKey
*/
public void delCacheMapValue(final String key, final String hKey)
{
HashOperations hashOperations = redisTemplate.opsForHash();
hashOperations.delete(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);
}
}
配置哨兵集群及读写分离
修改yaml
spring:
redis:
sentinel:
master: mymaster
nodes:
- 127.0.0.1:7001
- 127.0.0.1:7002
- 127.0.0.1:7003
logging:
pattern:
console: '%date{yyyy-MM-dd HH:mm:ss.SSS} | %highlight(%5level) [%green(%16.16thread)] %clr(%-50.50logger{49}){cyan} %4line -| %highlight(%msg%n)'
level:
root: info
修改RedisConfig
/**
* 读写分离:RedisConfig添加lettuceConnectionFactory配置
*
*/
@Configuration
@EnableCaching
public class RedisConfig extends CachingConfigurerSupport
{
@Bean
public RedisConnectionFactory lettuceConnectionFactory(RedisProperties redisProperties) {
RedisSentinelConfiguration redisSentinelConfiguration = new RedisSentinelConfiguration(
redisProperties.getSentinel().getMaster(), new HashSet<>(redisProperties.getSentinel().getNodes())
);
LettucePoolingClientConfiguration lettuceClientConfiguration = LettucePoolingClientConfiguration.builder()
// 读写分离,若主节点能抗住读写并发,则不需要设置,全都走主节点即可
.readFrom(ReadFrom.ANY_REPLICA)
.build();
return new LettuceConnectionFactory(redisSentinelConfiguration, lettuceClientConfiguration);
}
}
ReadFrom | 读取方式 |
---|---|
MASTER / UPSTREAM | 仅读取主节点 |
MASTER_PREFERRED / UPSTREAM_PREFERRED | 优先读取主节点,如果主节点不可用,则读取从节点 |
REPLICA / SLAVE (已废弃) | 仅读取从节点 |
REPLICA_PREFERRED / SLAVE_PREFERRED (已废弃) | 优先读取从节点,如果从节点不可用,则读取主节点 |
NEAREST | 从最近节点读取 |
ANY | 从任何节点读取 |
ANY_REPLICA | 从任意一个从节点读取 |