ReactivePipeline

<thinking>
Looking at ReactivePipeline's usage patterns from the article, I should break down:

1. Purpose:
- Allows writing sequential-looking code that executes asynchronously
- Manages dependencies between service calls
- Optimizes thread utilization
- Reduces code complexity vs raw CompletableFuture

2. Implementation considerations:
- Can be implemented using Java 8's CompletableFuture
- Need to show both simple and complex usage examples
- Should demonstrate error handling and timeout patterns
- Want to compare with traditional synchronous approach

3. Key features to highlight:
- Context sharing between tasks
- Dependency declaration
- Performance benefits
- Error handling
- Timeout management

Let me structure a practical response showing the implementation and usage patterns.
</thinking>

是的，ReactivePipeline完全可以用Java 8实现。我来展示具体的实现和使用方式：

1. 首先是基础实现：

```java
public class ReactivePipeline<T> {
private CompletableFuture<T> pipeline;
private Map<String, Object> context;

public ReactivePipeline(T initialValue) {
this.pipeline = CompletableFuture.completedFuture(initialValue);
this.context = new HashMap<>();
}

// 添加异步任务
public ReactivePipeline<T> addTask(Function<T, CompletableFuture<T>> task) {
pipeline = pipeline.thenComposeAsync(task);
return this;
}

// 添加超时控制
public ReactivePipeline<T> addTimeout(Duration timeout) {
pipeline = pipeline.orTimeout(timeout.toMillis(), TimeUnit.MILLISECONDS);
return this;
}

// 获取上下文
public Map<String, Object> getContext() {
return context;
}

// 获取结果
public T get() throws Exception {
return pipeline.get();
}
}
```

2. 实际使用示例(电商下单场景)：

```java
@Service
public class OrderService {
@Autowired
private ProductService productService;
@Autowired
private InventoryService inventoryService;
@Autowired
private PaymentService paymentService;

public OrderResult createOrder(OrderRequest request) {
OrderContext orderContext = new OrderContext(request);

// 创建pipeline并执行
ReactivePipeline<OrderContext> pipeline = new ReactivePipeline<>(orderContext)
// 查询商品信息
.addTask(ctx -> CompletableFuture.supplyAsync(() -> {
ProductInfo product = productService.getProduct(ctx.getProductId());
ctx.setProduct(product);
return ctx;
}))
// 检查库存
.addTask(ctx -> CompletableFuture.supplyAsync(() -> {
boolean hasStock = inventoryService.checkStock(ctx.getProductId(), ctx.getQuantity());
if (!hasStock) {
throw new OutOfStockException();
}
return ctx;
}))
// 预扣款
.addTask(ctx -> CompletableFuture.supplyAsync(() -> {
PaymentResult payment = paymentService.preAuth(ctx.getUserId(), ctx.getAmount());
ctx.setPaymentResult(payment);
return ctx;
}))
// 设置3秒超时
.addTimeout(Duration.ofSeconds(3));

try {
OrderContext result = pipeline.get();
return buildOrderResult(result);
} catch (Exception e) {
handleException(e);
}
}
}
```

3. 更复杂的并行任务处理：

```java
public class ReactivePipeline<T> {
// 添加并行任务
public ReactivePipeline<T> addParallelTasks(
List<Function<T, CompletableFuture<T>>> tasks) {
pipeline = pipeline.thenComposeAsync(value -> {
List<CompletableFuture<T>> futures = tasks.stream()
.map(task -> task.apply(value))
.collect(Collectors.toList());

return CompletableFuture.allOf(
futures.toArray(new CompletableFuture[0]))
.thenApply(v -> value);
});
return this;
}
}

// 使用示例
pipeline.addParallelTasks(Arrays.asList(
ctx -> updateInventory(ctx),
ctx -> updateUserPoints(ctx),
ctx -> sendNotification(ctx)
));
```

4. 错误处理增强：

```java
public class ReactivePipeline<T> {
// 添加异常处理
public ReactivePipeline<T> addErrorHandler(
Function<Throwable, T> errorHandler) {
pipeline = pipeline.exceptionally(errorHandler);
return this;
}

// 添加重试逻辑
public ReactivePipeline<T> withRetry(int maxAttempts, Duration delay) {
CompletableFuture<T> retryPipeline = pipeline;

for (int i = 1; i < maxAttempts; i++) {
retryPipeline = retryPipeline.exceptionally(ex -> {
try {
Thread.sleep(delay.toMillis());
return pipeline.get();
} catch (Exception e) {
throw new CompletionException(e);
}
});
}

pipeline = retryPipeline;
return this;
}
}