在實際的開發中,會有這樣的場景。有一個微服務須要提供一個查詢的服務,可是須要查詢的數據庫表的數據量十分龐大,查詢所須要的時間很長。
此時就能夠考慮在項目中加入緩存。java
在maven項目中引入以下依賴。而且須要在本地安裝redis。redis
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis</artifactId> <version>2.0.5.RELEASE</version> </dependency>
在SpringBoot的配置文件中添加以下代碼。spring
redis: host: 127.0.0.1 port: 6379 timeout: 5000 database: 0 jedis: pool: max-idle: 8 max-wait: min-idle: 0
新建名爲RedisConfig的配置類。數據庫
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.CachingConfigurerSupport; import org.springframework.cache.annotation.EnableCaching; import org.springframework.cache.interceptor.KeyGenerator; 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.cache.RedisCacheWriter; import org.springframework.data.redis.connection.RedisConnectionFactory; import org.springframework.data.redis.core.RedisTemplate; import org.springframework.data.redis.core.StringRedisTemplate; import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer; import java.time.Duration; /** * RedisConfig * * @author detectiveHLH * @date 2018-10-11 14:39 **/ @Configuration @EnableCaching public class RedisConfig extends CachingConfigurerSupport { @Bean @Override public KeyGenerator keyGenerator() { return (target, method, params) -> { StringBuilder sb = new StringBuilder(); sb.append(target.getClass().getName()); sb.append(method.getName()); for (Object obj : params) { sb.append(obj.toString()); } return sb.toString(); }; } @Bean public RedisTemplate<String, String> redisTemplate(RedisConnectionFactory factory) { ObjectMapper om = new ObjectMapper(); om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY); om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL); //redis序列化 Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class); jackson2JsonRedisSerializer.setObjectMapper(om); StringRedisTemplate template = new StringRedisTemplate(factory); template.setValueSerializer(jackson2JsonRedisSerializer); template.afterPropertiesSet(); return template; } /** * 自定義CacheManager */ @Bean public CacheManager cacheManager(RedisTemplate redisTemplate) { //全局redis緩存過時時間 RedisCacheConfiguration redisCacheConfiguration = RedisCacheConfiguration.defaultCacheConfig().entryTtl(Duration.ofDays(1)); RedisCacheWriter redisCacheWriter = RedisCacheWriter.nonLockingRedisCacheWriter(redisTemplate.getConnectionFactory()); return new RedisCacheManager(redisCacheWriter, redisCacheConfiguration); } }
在項目的service層中的實現類中,添加@Cacheable註解。api
import java.util.HashMap; /** * UserLoginServiceImpl * * @author detectiveHLH * @date 2018-10-10 17:20 **/ @Service public class UserLoginServiceImpl implements UserLoginService { @Autowired private UserLoginMapper userLoginMapper; @Override @Cacheable(value = "usercache") public HashMap getByUserName(String userName) { System.out.println("此時沒有走緩存"); return userLoginMapper.getByUserName(userName); } }
而後調用一次該接口。就能夠在redis中看到以下的key。緩存
"usercache::com.detectiveHLH.api.service.impl.UserLoginServiceImplgetByUserNameSolarFarm"
同時,能夠在控制檯中看到有"此時沒有走緩存"的輸出。而後再次調用該接口,就能夠看到返回的速度明顯變快,而且沒有"此時沒有走緩存"輸出。說明
此時的接口走的是緩存。app