在实际的开发项目中,一个对外暴露的接口往往会面临很多次请求,我们来解释一下幂等的概念:任意多次执行所产生的影响均与一次执行的影响相同。按照这个含义,最终的含义就是 对数据库的影响只能是一次性的,不能重复处理。如何保证其幂等性,通常有以下手段:
redis实现自动幂等的原理图:
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/** * redis工具类 */ @Component public class RedisService { @Autowired private RedisTemplate redisTemplate; /** * 写入缓存 * @param key * @param value * @return */ public boolean set(final String key, Object value) { boolean result = false; try { ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue(); operations.set(key, value); result = true; } catch (Exception e) { e.printStackTrace(); } return result; } /** * 写入缓存设置时效时间 * @param key * @param value * @return */ public boolean setEx(final String key, Object value, Long expireTime) { boolean result = false; try { ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue(); operations.set(key, value); redisTemplate.expire(key, expireTime, TimeUnit.SECONDS); result = true; } catch (Exception e) { e.printStackTrace(); } return result; } /** * 判断缓存中是否有对应的value * @param key * @return */ public boolean exists(final String key) { return redisTemplate.hasKey(key); } /** * 读取缓存 * @param key * @return */ public Object get(final String key) { Object result = null; ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue(); result = operations.get(key); return result; } /** * 删除对应的value * @param key */ public boolean remove(final String key) { if (exists(key)) { Boolean delete = redisTemplate.delete(key); return delete; } return false; } }
自定义一个注解,定义此注解的主要目的是把它添加在需要实现幂等的方法上,凡是某个方法注解了它,都会实现自动幂等。后台利用反射如果扫描到这个注解,就会处理这个方法实现自动幂等,使用元注解ElementType.METHOD表示它只能放在方法上,etentionPolicy.RUNTIME表示它在运行时
@Target({ElementType.METHOD}) @Retention(RetentionPolicy.RUNTIME) public @interface AutoIdempotent { }
public interface TokenService { /** * 创建token * @return */ public String createToken(); /** * 检验token * @param request * @return */ public boolean checkToken(HttpServletRequest request) throws Exception; }
@Service public class TokenServiceImpl implements TokenService { @Autowired private RedisService redisService; /** * 创建token * * @return */ @Override public String createToken() { String str = RandomUtil.randomUUID(); StrBuilder token = new StrBuilder(); try { token.append(Constant.Redis.TOKEN_PREFIX).append(str); redisService.setEx(token.toString(), token.toString(),10000L); boolean notEmpty = StrUtil.isNotEmpty(token.toString()); if (notEmpty) { return token.toString(); } }catch (Exception ex){ ex.printStackTrace(); } return null; } /** * 检验token * * @param request * @return */ @Override public boolean checkToken(HttpServletRequest request) throws Exception { String token = request.getHeader(Constant.TOKEN_NAME); if (StrUtil.isBlank(token)) {// header中不存在token token = request.getParameter(Constant.TOKEN_NAME); if (StrUtil.isBlank(token)) {// parameter中也不存在token throw new ServiceException(Constant.ResponseCode.ILLEGAL_ARGUMENT, 100); } } if (!redisService.exists(token)) { throw new ServiceException(Constant.ResponseCode.REPETITIVE_OPERATION, 200); } boolean remove = redisService.remove(token); if (!remove) { throw new ServiceException(Constant.ResponseCode.REPETITIVE_OPERATION, 200); } return true; } }
@Configuration public class WebConfiguration extends WebMvcConfigurerAdapter { @Resource private AutoIdempotentInterceptor autoIdempotentInterceptor; /** * 添加拦截器 * @param registry */ @Override public void addInterceptors(InterceptorRegistry registry) { registry.addInterceptor(autoIdempotentInterceptor); super.addInterceptors(registry); } }
/** * 拦截器 */ @Component public class AutoIdempotentInterceptor implements HandlerInterceptor { @Autowired private TokenService tokenService; /** * 预处理 * * @param request * @param response * @param handler * @return * @throws Exception */ @Override public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception { if (!(handler instanceof HandlerMethod)) { return true; } HandlerMethod handlerMethod = (HandlerMethod) handler; Method method = handlerMethod.getMethod(); //被ApiIdempotment标记的扫描 AutoIdempotent methodmethodAnnotation = method.getAnnotation(AutoIdempotent.class); if (methodAnnotation != null) { try { return tokenService.checkToken(request);// 幂等性校验, 校验通过则放行, 校验失败则抛出异常, 并通过统一异常处理返回友好提示 }catch (Exception ex){ ResultVo failedResult = ResultVo.getFailedResult(101, ex.getMessage()); writeReturnJson(response, JSONUtil.toJsonStr(failedResult)); throw ex; } } //必须返回true,否则会被拦截一切请求 return true; } @Override public void postHandle(HttpServletRequest request, HttpServletResponse response, Object handler, ModelAndView modelAndView) throws Exception { } @Override public void afterCompletion(HttpServletRequest request, HttpServletResponse response, Object handler, Exception ex) throws Exception { } /** * 返回的json值 * @param response * @param json * @throws Exception */ private void writeReturnJson(HttpServletResponse response, String json) throws Exception{ PrintWriter writer = null; response.setCharacterEncoding("UTF-8"); response.setContentType("text/html; charset=utf-8"); try { writer = response.getWriter(); writer.print(json); } catch (IOException e) { } finally { if (writer != null) writer.close(); } } }
@RestController public class BusinessController { @Resource private TokenService tokenService; @Resource private TestService testService; @PostMapping("/get/token") public String getToken(){ String token = tokenService.createToken(); if (StrUtil.isNotEmpty(token)) { ResultVo resultVo = new ResultVo(); resultVo.setCode(Constant.code_success); resultVo.setMessage(Constant.SUCCESS); resultVo.setData(token); return JSONUtil.toJsonStr(resultVo); } return StrUtil.EMPTY; } @AutoIdempotent @PostMapping("/test/Idempotence") public String testIdempotence() { String businessResult = testService.testIdempotence(); if (StrUtil.isNotEmpty(businessResult)) { ResultVo successResult = ResultVo.getSuccessResult(businessResult); return JSONUtil.toJsonStr(successResult); } return StrUtil.EMPTY; } }
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本篇博客介绍了使用springboot和拦截器、redis来优雅的实现接口幂等,对于幂等在实际的开发过程中是十分重要的,因为一个接口可能会被无数的客户端调用,如何保证其不影响后台的业务处理,如何保证其只影响数据一次是非常重要的,它可以防止产生脏数据或者乱数据,也可以减少并发量,实乃十分有益的一件事。而传统的做法是每次判断数据,这种做法不够智能化和自动化,比较麻烦。而今天的这种自动化处理也可以提升程序的伸缩性。
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