Spring Data Redis 是Spring 框架提供的用于操作Redis的方式,最近整理了下它的用法,解决了使用过程中遇到的一些难点与坑点,希望对大家有所帮助。本文涵盖了Redis的安装、Spring Cache结合Redis的使用、Redis连接池的使用和RedisTemplate的使用等内容。
Redis安装 这里提供Linux和Windows两种安装方式,由于Windows下的版本最高只有3.2版本,所以推荐使用Linux下的版本,目前最新稳定版本为5.0,也是本文中使用的版本。
Linux 这里我们使用Docker环境下的安装方式。
docker pull redis:5.0
docker run -p 6379:6379 --name redis \ -v /mydata/redis/data:/data \ -d redis:5.0 redis-server --appendonly yes
Windows 想使用Windows版本的朋友可以使用以下安装方式。
下载Windows版本的Redis,下载地址:https://github.com/MicrosoftArchive/redis/releases 在当前地址栏输入cmd后,执行redis的启动命令:redis-server.exe redis.windows.conf Spring Cache 操作Redis Spring Cache 简介 当Spring Boot 结合Redis来作为缓存使用时,最简单的方式就是使用Spring Cache了,使用它我们无需知道Spring中对Redis的各种操作,仅仅通过它提供的@Cacheable 、@CachePut 、@CacheEvict 、@EnableCaching等注解就可以实现缓存功能。
常用注解 @EnableCaching 开启缓存功能,一般放在启动类上。
@Cacheable 使用该注解的方法当缓存存在时,会从缓存中获取数据而不执行方法,当缓存不存在时,会执行方法并把返回结果存入缓存中。一般使用在查询方法上
,可以设置如下属性:
value:缓存名称(必填),指定缓存的命名空间; key:用于设置在命名空间中的缓存key值,可以使用SpEL表达式定义; unless:条件符合则不缓存; condition:条件符合则缓存。 @CachePut 使用该注解的方法每次执行时都会把返回结果存入缓存中。一般使用在新增方法上
,可以设置如下属性:
value:缓存名称(必填),指定缓存的命名空间; key:用于设置在命名空间中的缓存key值,可以使用SpEL表达式定义; unless:条件符合则不缓存; condition:条件符合则缓存。 @CacheEvict 使用该注解的方法执行时会清空指定的缓存。一般使用在更新或删除方法上
,可以设置如下属性:
value:缓存名称(必填),指定缓存的命名空间; key:用于设置在命名空间中的缓存key值,可以使用SpEL表达式定义; condition:条件符合则缓存。 使用步骤 <dependency > <groupId > org.springframework.bootgroupId ><artifactId > spring-boot-starter-data-redisartifactId >dependency >
修改配置文件application.yml,添加Redis的连接配置; spring: redis: host: 192.168 .6 .139 # Redis服务器地址 database: 0 # Redis数据库索引(默认为0) port: 6379 # Redis服务器连接端口 password: # Redis服务器连接密码(默认为空) timeout: 1000 ms # 连接超时时间
在启动类上添加@EnableCaching注解启动缓存功能; @EnableCaching @SpringBootApplication public class MallTinyApplication {public static void main (String[] args) { SpringApplication.run(MallTinyApplication.class, args); } }
接下来在PmsBrandServiceImpl类中使用相关注解来实现缓存功能,可以发现我们获取品牌详情的方法中使用了@Cacheable注解,在修改和删除品牌的方法上使用了@CacheEvict注解; /** * PmsBrandService实现类 * Created by macro on 2019/4/19. */ @Service public class PmsBrandServiceImpl implements PmsBrandService {@Autowired private PmsBrandMapper brandMapper;@CacheEvict (value = RedisConfig.REDIS_KEY_DATABASE, key = "'pms:brand:'+#id" )@Override public int update (Long id, PmsBrand brand) { brand.setId(id);return brandMapper.updateByPrimaryKeySelective(brand); }@CacheEvict (value = RedisConfig.REDIS_KEY_DATABASE, key = "'pms:brand:'+#id" )@Override public int delete (Long id) {return brandMapper.deleteByPrimaryKey(id); }@Cacheable (value = RedisConfig.REDIS_KEY_DATABASE, key = "'pms:brand:'+#id" , unless = "#result==null" )@Override public PmsBrand getItem (Long id) {return brandMapper.selectByPrimaryKey(id); } }
我们可以调用获取品牌详情的接口测试下效果,此时发现Redis中存储的数据有点像乱码,并且没有设置过期时间; 存储JSON格式数据 此时我们就会想到有没有什么办法让Redis中存储的数据变成标准的JSON格式,然后可以设置一定的过期时间,不设置过期时间容易产生很多不必要的缓存数据。
我们可以通过给RedisTemplate设置JSON格式的序列化器,并通过配置RedisCacheConfiguration设置超时时间来实现以上需求,此时别忘了去除启动类上的@EnableCaching注解,具体配置类RedisConfig代码如下; /** * Redis配置类 * Created by macro on 2020/3/2. */ @EnableCaching @Configuration public class RedisConfig extends CachingConfigurerSupport {/** * redis数据库自定义key */ public static final String REDIS_KEY_DATABASE="mall" ;@Bean public RedisTemplate redisTemplate (RedisConnectionFactory redisConnectionFactory) { RedisSerializer serializer = redisSerializer(); RedisTemplate redisTemplate = new RedisTemplate<>(); redisTemplate.setConnectionFactory(redisConnectionFactory); redisTemplate.setKeySerializer(new StringRedisSerializer()); redisTemplate.setValueSerializer(serializer); redisTemplate.setHashKeySerializer(new StringRedisSerializer()); redisTemplate.setHashValueSerializer(serializer); redisTemplate.afterPropertiesSet();return redisTemplate; }@Bean public RedisSerializer redisSerializer () {//创建JSON序列化器 Jackson2JsonRedisSerializer serializer = new Jackson2JsonRedisSerializer<>(Object.class); ObjectMapper objectMapper = new ObjectMapper(); objectMapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY); objectMapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL); serializer.setObjectMapper(objectMapper);return serializer; }@Bean public RedisCacheManager redisCacheManager (RedisConnectionFactory redisConnectionFactory) { RedisCacheWriter redisCacheWriter = RedisCacheWriter.nonLockingRedisCacheWriter(redisConnectionFactory);//设置Redis缓存有效期为1天 RedisCacheConfiguration redisCacheConfiguration = RedisCacheConfiguration.defaultCacheConfig() .serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(redisSerializer())).entryTtl(Duration.ofDays(1 ));return new RedisCacheManager(redisCacheWriter, redisCacheConfiguration); } }此时我们再次调用获取商品详情的接口进行测试,会发现Redis中已经缓存了标准的JSON格式数据,并且超时时间被设置为了1天。 使用Redis连接池 SpringBoot 1.5.x版本Redis客户端默认是Jedis实现的,SpringBoot 2.x版本中默认客户端是用Lettuce实现的,我们先来了解下Jedis和Lettuce客户端。
Jedis vs Lettuce Jedis在实现上是直连Redis服务,多线程环境下非线程安全,除非使用连接池,为每个 RedisConnection 实例增加物理连接。
Lettuce是一种可伸缩,线程安全,完全非阻塞的Redis客户端,多个线程可以共享一个RedisConnection,它利用Netty NIO框架来高效地管理多个连接,从而提供了异步和同步数据访问方式,用于构建非阻塞的反应性应用程序。
使用步骤 修改application.yml添加Lettuce连接池配置,用于配置线程数量和阻塞等待时间; spring: redis: lettuce: pool: max-active: 8 # 连接池最大连接数 max-idle: 8 # 连接池最大空闲连接数 min-idle: 0 # 连接池最小空闲连接数 max-wait: -1 ms # 连接池最大阻塞等待时间,负值表示没有限制
由于SpringBoot 2.x中默认并没有使用Redis连接池,所以需要在pom.xml中添加commons-pool2的依赖; <dependency > <groupId > org.apache.commonsgroupId ><artifactId > commons-pool2artifactId >dependency >
如果你没添加以上依赖的话,启动应用的时候就会产生如下错误; Caused by: java.lang.NoClassDefFoundError: org/apache/commons/pool2/impl/GenericObjectPoolConfig at org.springframework.data.redis.connection.lettuce.LettucePoolingClientConfiguration$LettucePoolingClientConfigurationBuilder .(LettucePoolingClientConfiguration.java:84) ~[spring-data-redis-2.1.5.RELEASE.jar:2.1.5.RELEASE] at org.springframework.data.redis.connection.lettuce.LettucePoolingClientConfiguration.builder(LettucePoolingClientConfiguration.java:48) ~[spring-data-redis-2.1.5.RELEASE.jar:2.1.5.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration$PoolBuilderFactory .createBuilder(LettuceConnectionConfiguration.java:149) ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration.createBuilder(LettuceConnectionConfiguration.java:107) ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration.getLettuceClientConfiguration(LettuceConnectionConfiguration.java:93) ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration.redisConnectionFactory(LettuceConnectionConfiguration.java:74) ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration$$EnhancerBySpringCGLIB $$5caa7e47 .CGLIB$redisConnectionFactory $0 () ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration$$EnhancerBySpringCGLIB $$5caa7e47 $$FastClassBySpringCGLIB $$b8ae2813 .invoke() ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at org.springframework.cglib.proxy.MethodProxy.invokeSuper(MethodProxy.java:244) ~[spring-core-5.1.5.RELEASE.jar:5.1.5.RELEASE] at org.springframework.context.annotation.ConfigurationClassEnhancer$BeanMethodInterceptor .intercept(ConfigurationClassEnhancer.java:363) ~[spring-context-5.1.5.RELEASE.jar:5.1.5.RELEASE] at org.springframework.boot.autoconfigure.data.redis.LettuceConnectionConfiguration$$EnhancerBySpringCGLIB $$5caa7e47 .redisConnectionFactory() ~[spring-boot-autoconfigure-2.1.3.RELEASE.jar:2.1.3.RELEASE] at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[na:1.8.0_91] at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[na:1.8.0_91] at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[na:1.8.0_91] at java.lang.reflect.Method.invoke(Method.java:498) ~[na:1.8.0_91] at org.springframework.beans.factory.support.SimpleInstantiationStrategy.instantiate(SimpleInstantiationStrategy.java:154) ~[spring-beans-5.1.5.RELEASE.jar:5.1.5.RELEASE] ... 111 common frames omitted
自由操作Redis Spring Cache 给我们提供了操作Redis缓存的便捷方法,但是也有很多局限性。比如说我们想单独设置一个缓存值的有效期怎么办?我们并不想缓存方法的返回值,我们想缓存方法中产生的中间值怎么办?此时我们就需要用到RedisTemplate这个类了,接下来我们来讲下如何通过RedisTemplate来自由操作Redis中的缓存。
RedisService 定义Redis操作业务类,在Redis中有几种数据结构,比如普通结构(对象),Hash结构、Set结构、List结构,该接口中定义了大多数常用操作方法。
/** * redis操作Service * Created by macro on 2020/3/3. */ public interface RedisService {/** * 保存属性 */ void set (String key, Object value, long time) ;/** * 保存属性 */ void set (String key, Object value) ;/** * 获取属性 */ Object get (String key) ;/** * 删除属性 */ Boolean del (String key) ;/** * 批量删除属性 */ Long del (List keys) ;/** * 设置过期时间 */ Boolean expire (String key, long time) ;/** * 获取过期时间 */ Long getExpire (String key) ;/** * 判断是否有该属性 */ Boolean hasKey (String key) ;/** * 按delta递增 */ Long incr (String key, long delta) ;/** * 按delta递减 */ Long decr (String key, long delta) ;/** * 获取Hash结构中的属性 */ Object hGet (String key, String hashKey) ;/** * 向Hash结构中放入一个属性 */ Boolean hSet (String key, String hashKey, Object value, long time) ;/** * 向Hash结构中放入一个属性 */ void hSet (String key, String hashKey, Object value) ;/** * 直接获取整个Hash结构 */ Map hGetAll (String key) ;/** * 直接设置整个Hash结构 */ Boolean hSetAll (String key, Map map, long time) ;/** * 直接设置整个Hash结构 */ void hSetAll (String key, Map map) ;/** * 删除Hash结构中的属性 */ void hDel (String key, Object... hashKey) ;/** * 判断Hash结构中是否有该属性 */ Boolean hHasKey (String key, String hashKey) ;/** * Hash结构中属性递增 */ Long hIncr (String key, String hashKey, Long delta) ;/** * Hash结构中属性递减 */ Long hDecr (String key, String hashKey, Long delta) ;/** * 获取Set结构 */ Set sMembers (String key) ;/** * 向Set结构中添加属性 */ Long sAdd (String key, Object... values) ;/** * 向Set结构中添加属性 */ Long sAdd (String key, long time, Object... values) ;/** * 是否为Set中的属性 */ Boolean sIsMember (String key, Object value) ;/** * 获取Set结构的长度 */ Long sSize (String key) ;/** * 删除Set结构中的属性 */ Long sRemove (String key, Object... values) ;/** * 获取List结构中的属性 */ List lRange (String key, long start, long end) ;/** * 获取List结构的长度 */ Long lSize (String key) ;/** * 根据索引获取List中的属性 */ Object lIndex (String key, long index) ;/** * 向List结构中添加属性 */ Long lPush (String key, Object value) ;/** * 向List结构中添加属性 */ Long lPush (String key, Object value, long time) ;/** * 向List结构中批量添加属性 */ Long lPushAll (String key, Object... values) ;/** * 向List结构中批量添加属性 */ Long lPushAll (String key, Long time, Object... values) ;/** * 从List结构中移除属性 */ Long lRemove (String key, long count, Object value) ; }RedisServiceImpl RedisService的实现类,使用RedisTemplate来自由操作Redis中的缓存数据。
/** * redis操作实现类 * Created by macro on 2020/3/3. */ @Service public class RedisServiceImpl implements RedisService {@Autowired private RedisTemplate redisTemplate;@Override public void set (String key, Object value, long time) { redisTemplate.opsForValue().set(key, value, time, TimeUnit.SECONDS); }@Override public void set (String key, Object value) { redisTemplate.opsForValue().set(key, value); }@Override public Object get (String key) {return redisTemplate.opsForValue().get(key); }@Override public Boolean del (String key) {return redisTemplate.delete(key); }@Override public Long del (List keys) {return redisTemplate.delete(keys); }@Override public Boolean expire (String key, long time) {return redisTemplate.expire(key, time, TimeUnit.SECONDS); }@Override public Long getExpire (String key) {return redisTemplate.getExpire(key, TimeUnit.SECONDS); }@Override public Boolean hasKey (String key) {return redisTemplate.hasKey(key); }@Override public Long incr (String key, long delta) {return redisTemplate.opsForValue().increment(key, delta); }@Override public Long decr (String key, long delta) {return redisTemplate.opsForValue().increment(key, -delta); }@Override public Object hGet (String key, String hashKey) {return redisTemplate.opsForHash().get(key, hashKey); }@Override public Boolean hSet (String key, String hashKey, Object value, long time) { redisTemplate.opsForHash().put(key, hashKey, value);return expire(key, time); }@Override public void hSet (String key, String hashKey, Object value) { redisTemplate.opsForHash().put(key, hashKey, value); }@Override public Map hGetAll (String key) {return redisTemplate.opsForHash().entries(key); }@Override public Boolean hSetAll (String key, Map map, long time) { redisTemplate.opsForHash().putAll(key, map);return expire(key, time); }@Override public void hSetAll (String key, Map map) { redisTemplate.opsForHash().putAll(key, map); }@Override public void hDel (String key, Object... hashKey) { redisTemplate.opsForHash().delete(key, hashKey); }@Override public Boolean hHasKey (String key, String hashKey) {return redisTemplate.opsForHash().hasKey(key, hashKey); }@Override public Long hIncr (String key, String hashKey, Long delta) {return redisTemplate.opsForHash().increment(key, hashKey, delta); }@Override public Long hDecr (String key, String hashKey, Long delta) {return redisTemplate.opsForHash().increment(key, hashKey, -delta); }@Override public Set sMembers (String key) {return redisTemplate.opsForSet().members(key); }@Override public Long sAdd (String key, Object... values) {return redisTemplate.opsForSet().add(key, values); }@Override public Long sAdd (String key, long time, Object... values) { Long count = redisTemplate.opsForSet().add(key, values); expire(key, time);return count; }@Override public Boolean sIsMember (String key, Object value) {return redisTemplate.opsForSet().isMember(key, value); }@Override public Long sSize (String key) {return redisTemplate.opsForSet().size(key); }@Override public Long sRemove (String key, Object... values) {return redisTemplate.opsForSet().remove(key, values); }@Override public List lRange (String key, long start, long end) {return redisTemplate.opsForList().range(key, start, end); }@Override public Long lSize (String key) {return redisTemplate.opsForList().size(key); }@Override public Object lIndex (String key, long index) {return redisTemplate.opsForList().index(key, index); }@Override public Long lPush (String key, Object value) {return redisTemplate.opsForList().rightPush(key, value); }@Override public Long lPush (String key, Object value, long time) { Long index = redisTemplate.opsForList().rightPush(key, value); expire(key, time);return index; }@Override public Long lPushAll (String key, Object... values) {return redisTemplate.opsForList().rightPushAll(key, values); }@Override public Long lPushAll (String key, Long time, Object... values) { Long count = redisTemplate.opsForList().rightPushAll(key, values); expire(key, time);return count; }@Override public Long lRemove (String key, long count, Object value) {return redisTemplate.opsForList().remove(key, count, value); } }RedisController 测试RedisService中缓存操作的Controller,大家可以调用测试下。
/** * Redis测试Controller * Created by macro on 2020/3/3. */ @Api (tags = "RedisController" , description = "Redis测试" )@Controller @RequestMapping ("/redis" )public class RedisController {@Autowired private RedisService redisService;@Autowired private PmsBrandService brandService;@ApiOperation ("测试简单缓存" )@RequestMapping (value = "/simpleTest" , method = RequestMethod.GET)@ResponseBody public CommonResult simpleTest () { List brandList = brandService.list(1 , 5 ); PmsBrand brand = brandList.get(0 ); String key = "redis:simple:" + brand.getId(); redisService.set(key, brand); PmsBrand cacheBrand = (PmsBrand) redisService.get(key);return CommonResult.success(cacheBrand); }@ApiOperation ("测试Hash结构的缓存" )@RequestMapping (value = "/hashTest" , method = RequestMethod.GET)@ResponseBody public CommonResult hashTest () { List brandList = brandService.list(1 , 5 ); PmsBrand brand = brandList.get(0 ); String key = "redis:hash:" + brand.getId(); Map value = BeanUtil.beanToMap(brand); redisService.hSetAll(key, value); Map cacheValue = redisService.hGetAll(key); PmsBrand cacheBrand = BeanUtil.mapToBean(cacheValue, PmsBrand.class, true );return CommonResult.success(cacheBrand); }@ApiOperation ("测试Set结构的缓存" )@RequestMapping (value = "/setTest" , method = RequestMethod.GET)@ResponseBody public CommonResult> setTest() { List brandList = brandService.list(1 , 5 ); String key = "redis:set:all" ; redisService.sAdd(key, (Object[]) ArrayUtil.toArray(brandList, PmsBrand.class)); redisService.sRemove(key, brandList.get(0 )); Set cachedBrandList = redisService.sMembers(key);return CommonResult.success(cachedBrandList); }@ApiOperation ("测试List结构的缓存" )@RequestMapping (value = "/listTest" , method = RequestMethod.GET)@ResponseBody public CommonResult> listTest() { List brandList = brandService.list(1 , 5 ); String key = "redis:list:all" ; redisService.lPushAll(key, (Object[]) ArrayUtil.toArray(brandList, PmsBrand.class)); redisService.lRemove(key, 1 , brandList.get(0 )); List cachedBrandList = redisService.lRange(key, 0 , 3 );return CommonResult.success(cachedBrandList); } }
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