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SpringBoot解决用户重复提交订单(方式三:通过Redis实现-升级版)

SpringBoot解决用户重复提交订单(方式三:通过Redis实现-升级版)

文章目录

  • 前言
  • 1、方案实践
    • 1.1、引入Redis依赖
    • 1.2、添加Redis环境配置
    • 1.3、编写服务验证逻辑,通过 aop 代理方式实现
    • 1.4、在相关的业务接口上,增加SubmitLimit注解即可
  • 2、小结

前言

在上一篇文章中,我们详细的介绍了随着下单流量逐渐上升,为了降低数据库的访问压力,通过请求唯一ID+Redis分布式锁来防止接口重复提交,流程图如下!
SpringBoot解决用户重复提交订单(方式三:通过Redis实现-升级版)
每次提交的时候,需要先调用后端服务获取请求唯一ID,然后才能提交。

对于这样的流程,不少的同学可能会感觉到非常鸡肋,尤其是单元测试,需要每次先获取submitToken值,然后才能提交!

能不能不用这么麻烦,直接服务端通过一些规则组合,生成本次请求唯一ID呢?

答案是可以的!

今天我们就一起来看看,如何通过服务端来完成请求唯一 ID 的生成?

1、方案实践

我们先来看一张图,这张图就是本次方案的核心流程图。
SpringBoot解决用户重复提交订单(方式三:通过Redis实现-升级版)

实现的逻辑,流程如下:

1.用户点击提交按钮,服务端接受到请求后,通过规则计算出本次请求唯一ID值
2.使用redis的分布式锁服务,对请求 ID 在限定的时间内尝试进行加锁,如果加锁成功,继续后续流程;如果加锁失败,说明服务正在处理,请勿重复提交
3.最后一步,如果加锁成功后,需要将锁手动释放掉,以免再次请求时,提示同样的信息
引入缓存服务后,防止重复提交的大体思路如上,实践代码如下!

1.1、引入Redis依赖

本次项目是基于SpringBoot版本进行构建,添加相关的redis依赖环境如下:

<!-- 引入springboot -->
<parent><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-parent</artifactId><version>2.1.0.RELEASE</version>
</parent>......<!-- Redis相关依赖包,采用jedis作为客户端 -->
<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-redis</artifactId><exclusions><exclusion><groupId>redis.clients</groupId><artifactId>jedis</artifactId></exclusion><exclusion><artifactId>lettuce-core</artifactId><groupId>io.lettuce</groupId></exclusion></exclusions>
</dependency>
<dependency><groupId>redis.clients</groupId><artifactId>jedis</artifactId>
</dependency>
<dependency><groupId>org.apache.commons</groupId><artifactId>commons-pool2</artifactId>
</dependency>

特别注意:由于每个项目环境不一样,具体的依赖包需要和工程版本号匹配!

1.2、添加Redis环境配置

在全局配置application.properties文件中,添加Redis相关服务配置如下

# Redis数据库索引(默认为0)
spring.redis.database=1
# Redis服务器地址
spring.redis.host=127.0.0.1
# Redis服务器连接端口
spring.redis.port=6379
# Redis服务器连接密码(默认为空)
spring.redis.password=
# Redis服务器连接超时配置
spring.redis.timeout=1000# 连接池配置
spring.redis.jedis.pool.max-active=8
spring.redis.jedis.pool.max-wait=1000
spring.redis.jedis.pool.max-idle=8
spring.redis.jedis.pool.min-idle=0
spring.redis.jedis.pool.time-between-eviction-runs=100

在使用redis之前,请确保redis服务器是启动状态,并且能正常访问!

1.3、编写服务验证逻辑,通过 aop 代理方式实现

首先创建一个@SubmitLimit注解,通过这个注解来进行方法代理拦截!

@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.METHOD})
@Documented
public @interface SubmitLimit {/*** 指定时间内不可重复提交(仅相对上一次发起请求时间差),单位毫秒* @return*/int waitTime() default 1000;/*** 指定请求头部key,可以组合生成签名* @return*/String[] customerHeaders() default {};/*** 自定义重复提交提示语* @return*/String customerTipMsg() default "";
}

编写方法代理服务,增加防止重复提交的验证,实现了逻辑如下!

@Order(1)
@Aspect
@Component
public class SubmitLimitAspect {private static final Logger LOGGER = LoggerFactory.getLogger(SubmitLimitAspect.class);/*** redis分割符*/private static final String REDIS_SEPARATOR = ":";/*** 默认锁对应的值*/private static final String DEFAULT_LOCK_VALUE = "DEFAULT_SUBMIT_LOCK_VALUE";/*** 默认重复提交提示语*/private static final String DEFAULT_TIP_MSG = "服务正在处理,请勿重复提交!";@Value("${spring.application.name}")private String applicationName;@Autowiredprivate RedisLockService redisLockService;/*** 方法调用环绕拦截*/@Around(value = "@annotation(com.example.submittoken.config.annotation.SubmitLimit)")public Object doAround(ProceedingJoinPoint joinPoint){HttpServletRequest request = getHttpServletRequest();if(Objects.isNull(request)){return ResResult.getSysError("请求参数不能为空!");}//获取注解配置的参数SubmitLimit submitLimit = getSubmitLimit(joinPoint);//组合生成key,通过key实现加锁和解锁String lockKey = buildSubmitLimitKey(joinPoint, request, submitLimit.customerHeaders());//尝试在指定的时间内加锁boolean lock = redisLockService.tryLock(lockKey, DEFAULT_LOCK_VALUE, Duration.ofMillis(submitLimit.waitTime()));if(!lock){String tipMsg = StringUtils.isEmpty(submitLimit.customerTipMsg()) ? DEFAULT_TIP_MSG : submitLimit.customerTipMsg();return ResResult.getSysError(tipMsg);}try {//继续执行后续流程return execute(joinPoint);} finally {//执行完毕之后,手动将锁释放redisLockService.releaseLock(lockKey, DEFAULT_LOCK_VALUE);}}/*** 执行任务* @param joinPoint* @return*/private Object execute(ProceedingJoinPoint joinPoint){try {return joinPoint.proceed();} catch (CommonException e) {return ResResult.getSysError(e.getMessage());} catch (Throwable e) {LOGGER.error("业务处理发生异常,错误信息:",e);return ResResult.getSysError(ResResultEnum.DEFAULT_ERROR_MESSAGE);}}/*** 获取请求对象* @return*/private HttpServletRequest getHttpServletRequest(){RequestAttributes ra = RequestContextHolder.getRequestAttributes();ServletRequestAttributes sra = (ServletRequestAttributes)ra;HttpServletRequest request = sra.getRequest();return request;}/*** 获取注解值* @param joinPoint* @return*/private SubmitLimit getSubmitLimit(JoinPoint joinPoint){MethodSignature methodSignature = (MethodSignature) joinPoint.getSignature();Method method = methodSignature.getMethod();SubmitLimit submitLimit = method.getAnnotation(SubmitLimit.class);return submitLimit;}/*** 组合生成lockKey* 生成规则:项目名+接口名+方法名+请求参数签名(对请求头部参数+请求body参数,取SHA1值)* @param joinPoint* @param request* @param customerHeaders* @return*/private String buildSubmitLimitKey(JoinPoint joinPoint, HttpServletRequest request, String[] customerHeaders){//请求参数=请求头部+请求bodyString requestHeader = getRequestHeader(request, customerHeaders);String requestBody = getRequestBody(joinPoint.getArgs());String requestParamSign = DigestUtils.sha1Hex(requestHeader + requestBody);String submitLimitKey = new StringBuilder().append(applicationName).append(REDIS_SEPARATOR).append(joinPoint.getSignature().getDeclaringType().getSimpleName()).append(REDIS_SEPARATOR).append(joinPoint.getSignature().getName()).append(REDIS_SEPARATOR).append(requestParamSign).toString();return submitLimitKey;}/*** 获取指定请求头部参数* @param request* @param customerHeaders* @return*/private String getRequestHeader(HttpServletRequest request, String[] customerHeaders){if (Objects.isNull(customerHeaders)) {return "";}StringBuilder sb = new StringBuilder();for (String headerKey : customerHeaders) {sb.append(request.getHeader(headerKey));}return sb.toString();}/*** 获取请求body参数* @param args* @return*/private String getRequestBody(Object[] args){if (Objects.isNull(args)) {return "";}StringBuilder sb = new StringBuilder();for (Object arg : args) {if (arg instanceof HttpServletRequest|| arg instanceof HttpServletResponse|| arg instanceof MultipartFile|| arg instanceof BindResult|| arg instanceof MultipartFile[]|| arg instanceof ModelMap|| arg instanceof Model|| arg instanceof ExtendedServletRequestDataBinder|| arg instanceof byte[]) {continue;}sb.append(JacksonUtils.toJson(arg));}return sb.toString();}
}

部分校验逻辑用到了redis分布式锁,具体实现逻辑如下:

/*** redis分布式锁服务类* 采用LUA脚本实现,保证加锁、解锁操作原子性**/
@Component
public class RedisLockService {/*** 分布式锁过期时间,单位秒*/private static final Long DEFAULT_LOCK_EXPIRE_TIME = 60L;@Autowiredprivate StringRedisTemplate stringRedisTemplate;/*** 尝试在指定时间内加锁* @param key* @param value* @param timeout 锁等待时间* @return*/public boolean tryLock(String key,String value, Duration timeout){long waitMills = timeout.toMillis();long currentTimeMillis = System.currentTimeMillis();do {boolean lock = lock(key, value, DEFAULT_LOCK_EXPIRE_TIME);if (lock) {return true;}try {Thread.sleep(1L);} catch (InterruptedException e) {Thread.interrupted();}} while (System.currentTimeMillis() < currentTimeMillis + waitMills);return false;}/*** 直接加锁* @param key* @param value* @param expire* @return*/public boolean lock(String key,String value, Long expire){String luaScript = "if redis.call('setnx', KEYS[1], ARGV[1]) == 1 then return redis.call('expire', KEYS[1], ARGV[2]) else return 0 end";RedisScript<Long> redisScript = new DefaultRedisScript<>(luaScript, Long.class);Long result = stringRedisTemplate.execute(redisScript, Collections.singletonList(key), value, String.valueOf(expire));return result.equals(Long.valueOf(1));}/*** 释放锁* @param key* @param value* @return*/public boolean releaseLock(String key,String value){String luaScript = "if redis.call('get', KEYS[1]) == ARGV[1] then return redis.call('del', KEYS[1]) else return 0 end";RedisScript<Long> redisScript = new DefaultRedisScript<>(luaScript, Long.class);Long result = stringRedisTemplate.execute(redisScript, Collections.singletonList(key),value);return result.equals(Long.valueOf(1));}
}

部分代码使用到了序列化相关类JacksonUtils,源码如下:

public class JacksonUtils {private static final Logger LOGGER = LoggerFactory.getLogger(JacksonUtils.class);private static final ObjectMapper objectMapper = new ObjectMapper();static {// 对象的所有字段全部列入objectMapper.setSerializationInclusion(JsonInclude.Include.ALWAYS);// 忽略未知的字段objectMapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);// 读取不认识的枚举时,当null值处理objectMapper.configure(DeserializationFeature.READ_UNKNOWN_ENUM_VALUES_AS_NULL, true);
//        序列化忽略未知属性objectMapper.configure(SerializationFeature.FAIL_ON_EMPTY_BEANS, false);//忽略字段大小写objectMapper.configure(MapperFeature.ACCEPT_CASE_INSENSITIVE_PROPERTIES, true);objectMapper.configure(JsonParser.Feature.AUTO_CLOSE_SOURCE, true);SimpleModule module = new SimpleModule();module.addSerializer(Long.class, ToStringSerializer.instance);module.addSerializer(Long.TYPE, ToStringSerializer.instance);objectMapper.registerModule(module);}public static String toJson(Object object) {if (object == null) {return null;}try {return objectMapper.writeValueAsString(object);} catch (Exception e) {LOGGER.error("序列化失败",e);}return null;}public static <T> T fromJson(String json, Class<T> classOfT) {if (json == null) {return null;}try {return objectMapper.readValue(json, classOfT);} catch (Exception e) {LOGGER.error("反序列化失败",e);}return null;}public static <T> T fromJson(String json, Type typeOfT) {if (json == null) {return null;}try {return objectMapper.readValue(json, objectMapper.constructType(typeOfT));} catch (Exception e) {LOGGER.error("反序列化失败",e);}return null;}
}

1.4、在相关的业务接口上,增加SubmitLimit注解即可

@RestController
@RequestMapping("order")
public class OrderController {@Autowiredprivate OrderService orderService;/*** 下单,指定请求头部参与请求唯一值计算* @param request* @return*/@SubmitLimit(customerHeaders = {"appId", "token"}, customerTipMsg = "正在加紧为您处理,请勿重复下单!")@PostMapping(value = "confirm")public ResResult confirmOrder(@RequestBody OrderConfirmRequest request){//调用订单下单相关逻辑orderService.confirm(request);return ResResult.getSuccess();}
}

其中最关键的一个步就是将唯一请求 ID 的生成,放在服务端通过组合来实现,在保证防止接口重复提交的效果同时,也可以显著的降低接口测试复杂度!

2、小结

本次方案相比于上一个方案,最大的改进点在于:将接口请求唯一 ID 的生成逻辑,放在服务端通过规则组合来实现,不需要前端提交接口的时候强制带上这个参数,在满足防止接口重复提交的要求同时,又能减少前端和测试提交接口的复杂度!

需要特别注意的是:使用redis的分布式锁,推荐单机环境,如果redis是集群环境,可能会导致锁短暂无效!

解决方式一:https://blog.csdn.net/weixin_47316183/article/details/130180165?spm=1001.2014.3001.5502
解决方式二:https://blog.csdn.net/weixin_47316183/article/details/130180299?spm=1001.2014.3001.5502
解决方式三:https://blog.csdn.net/weixin_47316183/article/details/130180446?spm=1001.2014.3001.5502

参考:https://www.cnblogs.com/dxflqm/p/16914651.html