DDD实践落地(三)

Aggregate(遵守不变性规则设计设计聚合边界,业务知识的内聚)

  • 核心聚合设计

DDD实践落地(三)_第1张图片
CQRS(读写隔离)

  • ReadonlyPayingOrder用于解决支付环节内的读场景问题(构造相较于ReadWritePayingOrder更轻量),例如收银台获取待付款金额、支付结果页获取支付结果信息

  • ReadWritePayingOrder响应PayingCommand、CancelCommand等事件,解决订单支付、取消相关问题

  • 通过实体划分实现读写隔离,聚焦订单支付域内的问题(取消、支付等)

Domain Event(一致性边界之外的通信解决方案,跨域通信)

  • 实体函数中变更自身数据同时生成相关的领域事件(数据变化和事件都伴随着实体,domain repository以及event handler分别处理数据持久化以及领域事件)

  • 同时结合实体隔离达到事件隔离的目标,比如拼团订单支付完成的事件必须通过拼团订单实体来构造,能够从根源上避免事件污染问题;

DDD实践落地(三)_第2张图片

/**
 * 领域实体
 */
@DomainEntity
@Slf4j
@ToString
public abstract class AbstractReadWritePayingOrder extends AbstractPayingOrder implements IChangeTraceableAggregate {
 /**
 * 订单支付
 */
 public void pay(OrderPayCommand orderPayCommand) {
 if (OrderState.isCanceled(this.orderDTO.getState())) {
 log.warn("order:{} is canceled! orderPayCommand:{}", orderPayCommand.getOrderNumber(), orderPayCommand);
 } else if (OrderState.isPaid(this.orderDTO.getState())) {
 //幂等
 addDomainEvent(new OrderPayFinishedEvent(this));
 } else if (OrderState.isInPaying(this.orderDTO.getState())) {
 if (isPayFull()) {
 //全额支付完成
 //生成支付完成事件
 addDomainEvent(new OrderPayFinishedEvent(this));
 } else {
 //部分支付完成...
 }
 }
 //超额支付检测
 if (isOverPaid()) {
 addDomainEvent(new OverPaidEvent(this));
 }
 }
 public void cancel(OrderCancelCommand orderCancelCommand) {
 //...
 }
}
/**
 * 领域事件处理,跨域通信(可实现为接口调用、消息发送)
 */
@Slf4j
@Component
public class OrderPayFinishedEventHandler implements IDomainEventHandler {
 @Autowired
 private KafkaJsonMessageService kafkaJsonMessageService;
 @Override
 @Subscribe
 public void handleDomainEvent(OrderPayFinishedEvent domainEvent) {
 //订单整体支付完成
 kafkaJsonMessageService.publish(QueueConfig.ORDER_PAY_FINISH_TOPIC, new Gson().toJson(domainEvent.getSimpleOrderInfo()));
 }
}

Domain Repository(面向聚合、实体设计而非数据)

@Slf4j
@Repository
public class PayingOrderRepository extends RepositorySupport {
 /**
 * 向上暴露聚合实体,隐藏聚合的数据获取方式 
 */
 @Override
 public AbstractReadWritePayingOrder onFind(String orderNumber) {
 return PayingOrderFactory.createPayingOrder(orderDTO, orderItemDTOs, totalPaidAmoint, productInfos);
 }
 public ReadonlyPayingOrder findReadonlyPayingOrder(String orderNumber) {
 return PayingOrderFactory.createReadonlyPayingOrder(orderDTO, orderItemDTOs, totalPaidAmount);
 }
 /**
 * 最小知识法则,通过变更追踪的技术方案构造稳定的持久化解决方案,从而不关心领域函数内具体变化的是什么字段,避免业务侵入
 */
 @Override
 @Transactional(rollbackFor = Exception.class)
 public void onUpdate(PayingOrderChangeInfo payingOrderChangeInfo) {
 //订单更新
 if (payingOrderChangeInfo.getUpdateOrderDTO() != null) {
 orderRepository.updateByPrimaryKeySelective(payingOrderChangeInfo.getUpdateOrderDTO());
 }
 //操作日志保存
 if (CollectionUtils.isNotEmpty(payingOrderChangeInfo.getInsertOrderChangeLog())) {
 orderHistory.batchInsert(payingOrderChangeInfo.getInsertOrderChangeLog());
 }
 }
}

Snapshot方案实践:在聚合查询完成后,调用IChangeTraceableAggregate#attach函数建立数据快照;

答案在风中,公众号:答案在风中的BlogDDD实践落地(二)

Domain Service(领域对象的调度、低业务侵入)

  • domain service 调度领域对象的职责,但不感知其具体实现细节

@Slf4j
@Service
public class PayingOrderDomainService {
 @Autowired
 private PayingOrderRepository payingOrderRepository;
 @Autowired
 private DomainEventBus domainEventBus;
 @Autowired
 private RedisLockService mainRedisLockService;
 @Autowired
 private TransactionUtil transactionUtil;
 /**
 * 支付事件处理
 */
 public void pay(OrderPayCommand orderPayCommand) {
 RedisLock redisLock = mainRedisLockService.buildLock(ShippingOrderDomainService.LOCK_SCOPE_ORDER, orderPayCommand.getOrderNumber(),
 ShippingOrderDomainService.LOCK_DEFAULT_TTL);
 AbstractReadWritePayingOrder payingOrder = redisLock.withr(() -> {
 AbstractReadWritePayingOrder innerPayingOrder = orderPayCommand.isFreePay() ? payingOrderRepository.findOrderForFreePay(orderPayCommand) :
 payingOrderRepository.find(orderPayCommand.getOrderNumber());
 //订单支付
 innerPayingOrder.pay(orderPayCommand);
 //事务优先提交
 transactionUtil.transaction(() -> payingOrderRepository.update(innerPayingOrder), Propagation.REQUIRES_NEW);
 return innerPayingOrder;
 }, () -> {
 throw new ServiceRuntimeException(OrderReturnCode.SYSTEM_BUSY_CODE, orderPayCommand.toString());
 });
 domainEventBus.publish(payingOrder);
 }
 /**
 * 取消订单
 */
 public void cancelOrder(@NonNull OrderCancelCommand orderCancelCommand) {
 RedisLock redisLock = mainRedisLockService.buildLock(ShippingOrderDomainService.LOCK_SCOPE_ORDER, orderCancelCommand.getOrderNumber(),
 ShippingOrderDomainService.LOCK_DEFAULT_TTL);
 AbstractReadWritePayingOrder payingOrder = redisLock
 .withr(() -> {
 AbstractReadWritePayingOrder innerPayingOrder = payingOrderRepository.find(orderCancelCommand.getOrderNumber());
 //取消订单
 innerPayingOrder.cancel(orderCancelCommand);
 //持久化
 transactionUtil.transaction(() -> payingOrderRepository.update(innerPayingOrder), Propagation.REQUIRES_NEW);
 return innerPayingOrder;
 }, () -> {
 throw new ServiceRuntimeException(OrderReturnCode.SYSTEM_BUSY_CODE, orderCancelCommand.toString());
 });
 //发送领域事件
 domainEventBus.publish(payingOrder);
 }
}

Domain Test(聚焦实体,通过领域实体的职责解决复杂的业务场景构造问题)

测试过程

  1. 基本数据准备用于构造基准测试实体

  2. 通过基准测试实体的领域函数模拟领域生命周期内的不同状态

  3. 以不同的状态下的实体,验证聚合设计时的不变性规则以及相应的领域事件

收益

由于我们将业务都内聚到了领域实体内部(从上面可以看到service和repository中已经做到了无业务侵入,已不再是我们的测试重点),因此我们得以聚焦于实体测试。

以支付订单为例,我们按照不同类型的订单我们准备了11个不同的订单实体,并通过执行领域实体的pay()、cancel()或者模拟三方支付回调修改已支付金额来叠加影响(我们可以自由组合得到不同类型的不同状态的订单),以覆盖了近400个测试场景。

转载请注明出处
image

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