Spring Boot整合Redis缓存全攻略

Spring Boot整合Redis缓存详解

Redis是一种高性能的内存数据库，常用于缓存、消息队列等场景。Spring Boot提供了对Redis的自动配置支持，通过简单的配置即可实现缓存功能。

添加依赖

在pom.xml中添加Spring Boot Redis Starter和缓存相关依赖：

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-cache</artifactId>
</dependency>

配置Redis连接

在application.properties或application.yml中配置Redis连接信息：

spring.redis.host=localhost
spring.redis.port=6379
spring.redis.password=
spring.redis.database=0

启用缓存支持

在Spring Boot主类上添加@EnableCaching注解：

@SpringBootApplication
@EnableCaching
public class Application {
    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }
}

配置Redis缓存管理器

创建Redis缓存配置类：

@Configuration
public class RedisCacheConfig {
    
    @Bean
    public RedisCacheManager cacheManager(RedisConnectionFactory factory) {
        RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig()
            .entryTtl(Duration.ofMinutes(30))  // 设置缓存默认过期时间
            .disableCachingNullValues();      // 不缓存null值
            
        return RedisCacheManager.builder(factory)
            .cacheDefaults(config)
            .transactionAware()
            .build();
    }
}

使用缓存注解

在Service层方法上使用缓存注解：

@Service
public class ProductService {
    
    @Cacheable(value = "products", key = "#id")
    public Product getProductById(Long id) {
        // 模拟数据库查询
        return findProductFromDB(id);
    }
    
    @CachePut(value = "products", key = "#product.id")
    public Product updateProduct(Product product) {
        // 更新数据库
        return updateProductInDB(product);
    }
    
    @CacheEvict(value = "products", key = "#id")
    public void deleteProduct(Long id) {
        // 从数据库删除
        deleteProductFromDB(id);
    }
}

自定义Key生成策略

实现KeyGenerator接口自定义缓存Key生成：

@Configuration
public class CacheConfig {
    
    @Bean
    public KeyGenerator customKeyGenerator() {
        return (target, method, params) -> {
            StringBuilder sb = new StringBuilder();
            sb.append(target.getClass().getSimpleName());
            sb.append(method.getName());
            Arrays.stream(params).forEach(param -> {
                if(param != null) {
                    sb.append(param.toString());
                }
            });
            return sb.toString();
        };
    }
}

缓存异常处理

实现CacheErrorHandler处理缓存异常：

public class CustomCacheErrorHandler implements CacheErrorHandler {
    
    @Override
    public void handleCacheGetError(RuntimeException exception, Cache cache, Object key) {
        // 处理获取缓存异常
    }
    
    @Override
    public void handleCachePutError(RuntimeException exception, Cache cache, Object key, Object value) {
        // 处理放入缓存异常
    }
    
    @Override
    public void handleCacheEvictError(RuntimeException exception, Cache cache, Object key) {
        // 处理清除缓存异常
    }
    
    @Override
    public void handleCacheClearError(RuntimeException exception, Cache cache) {
        // 处理清空缓存异常
    }
}

多级缓存实现

结合本地缓存和Redis实现多级缓存：

@Configuration
public class MultiLevelCacheConfig {
    
    @Primary
    @Bean
    public CacheManager caffeineCacheManager() {
        CaffeineCacheManager cacheManager = new CaffeineCacheManager();
        cacheManager.setCaffeine(Caffeine.newBuilder()
            .expireAfterWrite(10, TimeUnit.MINUTES)
            .maximumSize(1000));
        return cacheManager;
    }
    
    @Bean
    public CacheManager redisCacheManager(RedisConnectionFactory factory) {
        RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig()
            .entryTtl(Duration.ofHours(1));
            
        return RedisCacheManager.builder(factory)
            .cacheDefaults(config)
            .build();
    }
    
    @Bean
    public CacheManager multiLevelCacheManager(
            @Qualifier("caffeineCacheManager") CacheManager caffeineCacheManager,
            @Qualifier("redisCacheManager") CacheManager redisCacheManager) {
        return new MultiLevelCacheManager(caffeineCacheManager, redisCacheManager);
    }
}

缓存预热实现

实现ApplicationRunner在应用启动时预热缓存：

@Component
public class CacheWarmUp implements ApplicationRunner {
    
    @Autowired
    private ProductService productService;
    
    @Override
    public void run(ApplicationArguments args) {
        // 预热热门商品缓存
        List<Long> hotProductIds = getHotProductIdsFromDB();
        hotProductIds.forEach(productService::getProductById);
    }
}

缓存监控

通过Redis命令或Spring Boot Actuator监控缓存状态：

management.endpoints.web.exposure.include=health,info,caches
management.endpoint.caches.enabled=true

性能优化建议

合理设置缓存过期时间，避免缓存雪崩
对热点数据使用多级缓存
大对象考虑压缩后存储
批量操作使用管道技术
监控缓存命中率调整缓存策略

常见问题解决

缓存穿透：使用布隆过滤器或缓存空值
缓存雪崩：设置随机过期时间或使用锁机制
缓存击穿：使用互斥锁或永不过期策略
数据一致性：采用双写策略或消息队列同步

通过以上步骤和配置，可以在Spring Boot应用中高效地集成Redis缓存，显著提升系统性能。实际应用中应根据业务场景调整缓存策略和配置参数。

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