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。
