springboot+redis缓存的实现方案
作者:李晨豪 Lch
本文介绍了Spring Boot与Redis结合实现缓存的三种方案:注解方式、注解切面类方式和使用样例,通过这些方案,可以有效地提高应用程序的性能和响应速度
springboot+redis缓存方案
一、注解
import java.lang.annotation.ElementType; import java.lang.annotation.Retention; import java.lang.annotation.RetentionPolicy; import java.lang.annotation.Target; import java.util.concurrent.TimeUnit; /** * @author lch * @date 2023/8/03 09:29 */ @Target(ElementType.METHOD) @Retention(RetentionPolicy.RUNTIME) public @interface RedisCache { /** * key,支持 spring el表达式 */ String key(); /** * 统一格式:服务名:场景,如:info */ String prefix(); /** * 过期时间 */ int expireTime() default 36000; /** * 时间单位 */ TimeUnit timeunit() default TimeUnit.SECONDS; }
二、注解切面类
import com.dewav.tms.framework.aspectj.lang.annotation.RedisCache; import com.dewav.tms.framework.redis.RedisService; import lombok.extern.slf4j.Slf4j; import org.aspectj.lang.ProceedingJoinPoint; import org.aspectj.lang.annotation.Around; import org.aspectj.lang.annotation.Aspect; import org.aspectj.lang.reflect.MethodSignature; import org.springframework.context.expression.MethodBasedEvaluationContext; import org.springframework.core.DefaultParameterNameDiscoverer; import org.springframework.expression.EvaluationContext; import org.springframework.expression.Expression; import org.springframework.expression.spel.standard.SpelExpressionParser; import org.springframework.stereotype.Component; import org.springframework.util.Assert; import javax.annotation.Resource; import java.lang.reflect.Method; import java.util.concurrent.TimeUnit; /** * @author lch * @date 2023/8/03 09:29 */ @Component @Aspect @Slf4j public class RedisCacheAspect { private final SpelExpressionParser spelExpressionParser = new SpelExpressionParser(); private final DefaultParameterNameDiscoverer parameterNameDiscoverer = new DefaultParameterNameDiscoverer(); @Resource private RedisService redisService; @Around("@annotation(redisCache)") public Object queryByRedisCache(ProceedingJoinPoint pjp, RedisCache redisCache) { int expireTime = redisCache.expireTime(); String key = redisCache.key(); String prefix = redisCache.prefix(); Assert.hasText(key, "@RedisCache key不能为空!"); Assert.hasText(prefix, "@RedisCache prefix不能为空!"); String evaluateExpression = evaluateExpression(key, pjp); String redisKey = prefix + evaluateExpression; Object obj = null; try { if (null != redisKey){ if (redisService.hasKey(redisKey)){ obj = redisService.getCacheObject(redisKey); return obj; } } } catch (Exception e) { log.error("从Redis获取"+redisKey+"失败:"+e.getMessage()); } try{ obj = pjp.proceed(); }catch(Throwable e){ log.error("执行异常", e); throw new RuntimeException(e.getMessage()); } if (null != redisKey){ redisService.setCacheObject(redisKey, obj, expireTime, TimeUnit.SECONDS); } return obj; } /** * 解析el表达式 * * @param expression * @param point * @return */ private String evaluateExpression(String expression, ProceedingJoinPoint point) { // 获取目标对象 Object target = point.getTarget(); // 获取方法参数 Object[] args = point.getArgs(); MethodSignature methodSignature = (MethodSignature) point.getSignature(); Method method = methodSignature.getMethod(); EvaluationContext context = new MethodBasedEvaluationContext(target, method, args, parameterNameDiscoverer); Expression exp = spelExpressionParser.parseExpression(expression); return exp.getValue(context, String.class); } }
三、使用样例
@Override @RedisCache(key = "{#customerId + ':' + #dictType}", prefix = CacheConstants.SYS_DICT_KEY) public List<SysDictData> selectDictDataByType(Long customerId, String dictType) { return dictDataMapper.selectDictDataByType(customerId, dictType); } @Override @RedisCache(key = "#apiKey", prefix = CacheConstants.OPEN_KEY + "apiInfo:apiKey:") public EdiApiInfo getByApiKey(String apiKey) { return baseMapper.selectOne(new QueryWrapper<EdiApiInfo>() .eq("api_key", apiKey) .eq("status", true) .eq("del_flag", false)); }
总结
以上为个人经验,希望能给大家一个参考,也希望大家多多支持脚本之家。