重试机制与 CompletableFuture 拓展

重试机制与 CompletableFuture 拓展

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本文旨在讨论重试机制的特点和策略,分析常用重试类库的实现,讨论为 CompletableFuture 添加重试机制的方法。文章首发同名公众号,欢迎关注。

重试示例

以下是一个常见的使用异步重试的例子,当我们需要重试功能时,只需调用 retry 方法,传入相应的重试策略即可。这里的重试策略为重试 2 次,使用回退策略(backoff),重试间隔为 100ms,抖动因子为 0.75,同时指定了调度器。

// Project Reactor 提供的重试方法
public Mono<String> getUsername(String userId) {
  	// backoff 重试策略
    var backoffRetry = Retry
        .backoff(2, Duration.ofMillis(100))
        .jitter(0.75)
        .scheduler(Schedulers.newSingle("retry scheduler"));
    return webClient.get()
        .uri("localhost:8080/user/", userId)
        .accept(MediaType.APPLICATION_JSON)
        .retrieve()
        .bodyToMono(String.class)
      	// 若为简单重试可改为调用 retry(n)
        .retryWhen(backoffRetry);
}

以下图片摘自 Mono#retryWhen 文档注释

file
Project Reactor 是基于发布-订阅模型的响应式组件。从图中可以看出,每次获取数据失败后,会等待一段时间,然后再次订阅发布者以获取数据,反复以上过程直到达到最终重试次数或者出现成功结果。

Spring Retry 类库提供了重试模版:

RetryTemplate template = RetryTemplate.builder()
				.maxAttempts(3)
				.fixedBackoff(1000)
				.retryOn(RemoteAccessException.class)
				.build();
// 重试
template.execute(ctx -> {
    // ... do something
});

重试模版需要传入任务,而 Project Reactor 中发布者-订阅者两者解耦,可以实现多次订阅,因此不影响链式调用。

若想为 CompletableFuture 增加重试功能,最好是使用类似 Spring-Retry 的模式,添加工具类方法 retry,参数包括任务、重试策略等。

重试策略

  1. 触发重试策略

    特定异常(如支持黑白名单)、特定返回值、自定义

  2. 等待策略(backoff 算法)

    无等待、固定时间(fixed)、等量增长时间(incremental)、指数增长时间(exponentail backoff)、随机时间(random)、斐波那契数列(fibnonacci) 、自定义

  3. 终止策略

    尝试次数(maxAttempts)、超时终止、自定义

重试策略应该注意区分有状态重试和无状态重试:

有状态重试表示各个重试之间存在相互依赖,比如

  1. 每次访问网站信息时,返回错误信息包含了下一次可以正常访问的时间

  2. 输入密码多次错误后,需要等待若干时间再重试

  3. 共用相同的限流组件;

无状态重试表示每次重试不依赖其他重试的结果,实现容易,某些复杂的有状态重试可以使用无状态重试实现。

重试上下文信息

常见的重试上下文有:重试次数、每次返回结果、日志记录、回调。

回调方法包括每次返回结果时回调、最终返回结果时回调。

简易实现代码

手动实现最简单的方法是调用 exceptionally 或者 exceptionallyCompose 方法,多次传入重试任务。

1. 迭代实现 N 次重试

以下代码使用了迭代法,缺点是造成 CompletableFuture 内部维护的 stack 过深,增加不必要的内存开销;无法实现无限次重试。

public static <T> CompletableFuture<T> retry(Supplier<T> supplier, int attempts) {
    var cf = supplyAsync(supplier);
    for (int i = 0; i < attempts; i++) {
        cf = cf.exceptionally(ex -> supplier.get());
    }
    return cf;
}

2. 递归实现 N 次重试

使用递归解决了以上问题:

@Slf4j
class RetryNAttemptsDemo {
  	// 演示用,忽略线程池配置
    public static void main(String[] args) {
      	// 任务3次重试后返回正确结果
        var times = new AtomicInteger();
        Supplier<Integer> task = () -> {
            if (times.getAndIncrement() < 3) {
                throw new RuntimeException("异常结果");
            } else {
                return 42;
            }
        };
      	// 使用重试
        retry(4, () -> supplyAsync(task))
            .thenAcceptAsync(r -> log.info("获取结果: {}", r))
            .whenComplete((__, ex) -> log.error("最终获取结果异常", ex))
            .join();
    }

    public static <T> CompletableFuture<T> retry(int attempts, Supplier<CompletionStage<T>> supplier) {
      	// 使用CompletableFuture的写功能
        var result = new CompletableFuture<T>();
        retryNAttempts(result, attempts, supplier);
        return result;
    }

    private static <T> void retryNAttempts(CompletableFuture<T> result, int attempts, Supplier<CompletionStage<T>> supplier) {
        supplier.get()
            .thenAccept(result::complete)
            .whenComplete((__, throwable) -> {
                if (attempts > 0L) {
                    log.warn("异常重试");
                    retryNAttempts(result, attempts - 1, supplier);
                } else {
                    log.error("多次重试异常结果", throwable);
                    result.completeExceptionally(throwable);
                }
            });
    }
}

执行结果如下,符合预期。

> Task :RetryNAttemptsDemo.main()
23:18:32.042 [main] WARN com.example.demo.futures.RetryNAttemptsDemo -- 异常重试
23:18:32.043 [main] WARN com.example.demo.futures.RetryNAttemptsDemo -- 异常重试
23:18:32.044 [main] WARN com.example.demo.futures.RetryNAttemptsDemo -- 异常重试
23:18:32.044 [ForkJoinPool.commonPool-worker-1] INFO com.example.demo.futures.RetryNAttemptsDemo -- 获取结果: 42

3. 递归实现 backoff

思路:

  1. 正常结果和异常结果分别处理,若有最终结果则记录到 result
  2. 处理结果为重试等待时间
  3. 执行重试(使用 ScheduledExecutorService#schedule)
@Slf4j
class BackoffRetryDemo {

    public static final long STOP_RETRY = -1L;
  
    private final int maxAttempts;
    private final AtomicInteger attempts = new AtomicInteger();
    // 延迟时间(ms)
    private final long delay;

    BackoffRetryDemo(int maxAttempts, long delay) {
        this.maxAttempts = maxAttempts;
        this.delay = delay;
    }

    public <T> CompletableFuture<T> retry(Supplier<CompletionStage<T>> stageSupplier, ScheduledExecutorService delayer) {
        CompletableFuture<T> result = new CompletableFuture<>();
        retry(stageSupplier, delayer, result);
        return result;
    }

    private <T> void retry(Supplier<CompletionStage<T>> stageSupplier, ScheduledExecutorService delayer, CompletableFuture<T> result) {
        attempts.incrementAndGet();
        stageSupplier.get()
            .thenApply(r -> {
                result.complete(r);
                return STOP_RETRY;
            })
            .exceptionally(throwable -> {
                if (attempts.get() >= maxAttempts) {
                    result.completeExceptionally(throwable);
                    return STOP_RETRY;
                }
                log.warn("异常重试");
                return delay;
            })
            .thenAccept(delay -> {
                if (delay == 0L)
                    delayer.execute(() -> retry(stageSupplier, delayer, result));
                else if (delay > 0L)
                    delayer.schedule(() -> retry(stageSupplier, delayer, result), delay, TimeUnit.MILLISECONDS);
            });
    }

    public static void main(String[] args) {
        var times = new AtomicInteger();
        Supplier<Integer> task = () -> {
            if (times.getAndIncrement() < 3) {
                throw new RuntimeException("异常结果");
            } else {
                return 42;
            }
        };

        var backoffRetry = new BackoffRetryDemo(4, 500);
        backoffRetry.retry(() -> supplyAsync(task), Executors.newSingleThreadScheduledExecutor())
            .thenAcceptAsync(r -> log.info("获取结果: {}", r))
            .exceptionallyAsync(throwable -> {
                log.error("最终获取结果异常", throwable);
                return null;
            })
            .join();
    }
}

执行日志如下:

> Task :BackoffRetryDemo.main()
23:54:12.099 [main] WARN com.example.demo.futures.BackoffRetryDemo -- 异常重试
23:54:12.610 [pool-1-thread-1] WARN com.example.demo.futures.BackoffRetryDemo -- 异常重试
23:54:13.113 [ForkJoinPool.commonPool-worker-1] WARN com.example.demo.futures.BackoffRetryDemo -- 异常重试
23:54:13.621 [ForkJoinPool.commonPool-worker-1] INFO com.example.demo.futures.BackoffRetryDemo -- 获取结果: 42

从结果可以看出,实现了延迟重试,重试等待时间为 500ms,三次尝试后获取到了正确结果。

不同类库的实现浅析

1. Resiliance4J

将 Retry 视为高阶函数装饰器,可以实现对任意方法的增强,如 Supplier, Consumer, CompletableFuture

CheckedFunction0<String> retryableSupplier = Retry
  .decorateCheckedSupplier(retry, helloWorldService::sayHelloWorld);
// 线程安全类
public interface Retry {
  	// 装饰器方法,为 supplier 增加可重试功能
    static <T> Supplier<CompletionStage<T>> decorateCompletionStage(
        Retry retry,
        ScheduledExecutorService scheduler,
        Supplier<CompletionStage<T>> supplier
    ) {
        return () -> {
          	// 这里使用 final 可能是为了兼容 JDK7
            final CompletableFuture<T> promise = new CompletableFuture<>();
            final Runnable block = new AsyncRetryBlock<>(scheduler, retry.asyncContext(), supplier,
                promise);
            block.run();
            return promise;
        };
    }
  
  	// 全局管理 Retry 支持
    String getName();
  	Map<String, String> getTags();
  	// 上下文支持回调
    <T> Retry.Context<T> context();
    <T> Retry.AsyncContext<T> asyncContext();
  	// 重试策略
    RetryConfig getRetryConfig();
    // 事件支持
    EventPublisher getEventPublisher();
  	
    default <T> CompletionStage<T> executeCompletionStage(ScheduledExecutorService scheduler,
                                                          Supplier<CompletionStage<T>> supplier) {
        return decorateCompletionStage(this, scheduler, supplier).get();
    }
  	// 略去其他执行方法,如 executeSupplier,executeRunnable
  
		// 监控信息
    Metrics getMetrics();
    interface Metrics {
        long getNumberOfSuccessfulCallsWithoutRetryAttempt();
        long getNumberOfFailedCallsWithoutRetryAttempt();
        long getNumberOfSuccessfulCallsWithRetryAttempt();
        long getNumberOfFailedCallsWithRetryAttempt();
    }
		// 回调支持
    interface AsyncContext<T> {
        void onComplete();
        long onError(Throwable throwable);
        long onResult(T result);
    }
    interface Context<T> {
        void onComplete();
        boolean onResult(T result);
        void onError(Exception exception) throws Exception;
        void onRuntimeError(RuntimeException runtimeException);
    }
		
  	// 事件支持,发布订阅模式,实现回调或者异步的另一种机制,发布者和订阅者(消费者)解耦
    interface EventPublisher extends io.github.resilience4j.core.EventPublisher<RetryEvent> {
        EventPublisher onRetry(EventConsumer<RetryOnRetryEvent> eventConsumer);
        EventPublisher onSuccess(EventConsumer<RetryOnSuccessEvent> eventConsumer);
        EventPublisher onError(EventConsumer<RetryOnErrorEvent> eventConsumer);
        EventPublisher onIgnoredError(EventConsumer<RetryOnIgnoredErrorEvent> eventConsumer);
    }
		// 这个类不知为何放在接口里面,实际上可以提出来
    class AsyncRetryBlock<T> implements Runnable {
      	// 下一部分分析
    }
}

不过异步增强的 CompletableFuture 不支持 Error 类型 fallback,封装了异步执行逻辑,实现逻辑和上一节 backoff 简易实现一致。

class AsyncRetryBlock<T> implements Runnable {
    private final ScheduledExecutorService scheduler;
  	// 调用其回调方法 onResult, onError
    private final Retry.AsyncContext<T> retryContext;
    private final Supplier<CompletionStage<T>> supplier;
  	// 最终结果,使用 CompletableFuture 的写功能
    private final CompletableFuture<T> promise;

  	// 略去构造器代码
    @Override
    public void run() {
        final CompletionStage<T> stage = supplier.get();
        stage.whenComplete((result, throwable) -> {
            if (throwable != null) {
              	// 支持 Exception 类型 fallback
                if (throwable instanceof Exception) {
                    onError((Exception) throwable);
                } else {
                    promise.completeExceptionally(throwable);
                }
            } else {
                onResult(result);
            }
        });
    }
		
  	// 重试或结束
    private void onError(Exception t) {
        final long delay = retryContext.onError(t);
        if (delay < 1) {
            promise.completeExceptionally(t);
        } else {
            scheduler.schedule(this, delay, TimeUnit.MILLISECONDS);
        }
    }

  	// 重试或结束
    private void onResult(T result) {
        final long delay = retryContext.onResult(result);
        if (delay < 1) {
            try {
                retryContext.onComplete();
                promise.complete(result);
            } catch (Exception e) {
                promise.completeExceptionally(e);
            }
        } else {
            scheduler.schedule(this, delay, TimeUnit.MILLISECONDS);
        }
    }
}

再来看 Context 的具体实现,总结为以下几点:

  1. 记录执行统计信息(如 numOfAttempts, lastException, succeededWithoutRetryCounter)
  2. 发布相关事件(publishRetryEvent)
  3. 每次执行前后支持回调, 如 consumeResultBeforeRetryAttempt
  4. 代码执行时调用 RetryConfig 指定的策略(策略模式)
// RetryImpl 的内部类, RetryImpl 持有统计信息相关字段,重试策略相关字段
public final class AsyncContextImpl implements Retry.AsyncContext<T> {

    private final AtomicInteger numOfAttempts = new AtomicInteger(0);
    private final AtomicReference<Throwable> lastException = new AtomicReference<>();

    @Override
    public long onError(Throwable throwable) {
        totalAttemptsCounter.increment();
        // Handle the case if the completable future throw CompletionException wrapping the original exception
        // where original exception is the one to retry not the CompletionException.
      	// 异常解包
        if (throwable instanceof CompletionException || throwable instanceof ExecutionException) {
            Throwable cause = throwable.getCause();
            return handleThrowable(cause);
        } else {
            return handleThrowable(throwable);
        }
    }
		
  	// handleThrowable 和 handleOnError 做了类似的逻辑,从名字上无法区分,还不如直接合并成一个方法
    private long handleThrowable(Throwable throwable) {
      	// 自定义方法判断是否需要 retry,exceptionPredicate 来自 RetryConfig
        if (!exceptionPredicate.test(throwable)) {
            failedWithoutRetryCounter.increment();
            publishRetryEvent(() -> new RetryOnIgnoredErrorEvent(getName(), throwable));
            return -1;
        }
        return handleOnError(throwable);
    }

    private long handleOnError(Throwable throwable) {
        lastException.set(throwable);
        int attempt = numOfAttempts.incrementAndGet();
        if (attempt >= maxAttempts) {
            failedAfterRetryCounter.increment();
            publishRetryEvent(() -> new RetryOnErrorEvent(name, attempt, throwable));
            return -1;
        }
				// backoff 策略, 来自 RetryConfig
        long interval = intervalBiFunction.apply(attempt, Either.left(throwable));
        if (interval < 0) {
            publishRetryEvent(() -> new RetryOnErrorEvent(getName(), attempt, throwable));
        } else {
            publishRetryEvent(() -> new RetryOnRetryEvent(getName(), attempt, throwable, interval));
        }
        return interval;
    }
  	// 略去其他方法
}

2. Spring Retry

这里不讨论 AOP 实现的重试增强,仅讨论命令式代码实现。

Spring Retry 实现了有状态的重试,很多方法需要显式传参数 RetryContext,有多种 RetryContext 支持,RetrySynchronizationManager 提供了全局 RetryContext 上下文支持,底层使用 ThreadLocal,提供获取上下文、注册上下文等方法。

任务封装为 RetryCallback,不直接支持 CompletableFuture。

// 封装的重试任务
public interface RetryCallback<T, E extends Throwable> {
		// 无状态重试不需要使用context
    /**
     * Execute an operation with retry semantics.
     */
    T doWithRetry(RetryContext context) throws E;

    /**
     * A logical identifier for this callback to distinguish retries around business
     * operations.
     */
    default String getLabel() {
       return null;
    }
}

RetryOperation 定义了重试操作:

public interface RetryOperations {
	<T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback) throws E;
	<T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback, RecoveryCallback<T> recoveryCallback) throws E;
	<T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback, RetryState retryState) throws E, ExhaustedRetryException;
	<T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback, RecoveryCallback<T> recoveryCallback, RetryState retryState) throws E;
}

回调接口定义了回调操作:

public interface RetryListener {
		// 开始重试时回调
    /**
     * Called before the first attempt in a retry. For instance, implementers can set up
     * state that is needed by the policies in the {@link RetryOperations}. The whole
     * retry can be vetoed by returning false from this method, in which case a
     * {@link TerminatedRetryException} will be thrown.
     */
    default <T, E extends Throwable> boolean open(RetryContext context, RetryCallback<T, E> callback) {
       return true;
    }
		
		// 结束重试时回调
    /**
     * Called after the final attempt (successful or not). Allow the listener to clean up
     * any resource it is holding before control returns to the retry caller.
     */
    default <T, E extends Throwable> void close(RetryContext context, RetryCallback<T, E> callback,
          Throwable throwable) {
    }

		// 成功时回调
    /**
     * Called after a successful attempt; allow the listener to throw a new exception to
     * cause a retry (according to the retry policy), based on the result returned by the
     * {@link RetryCallback#doWithRetry(RetryContext)}
     */
    default <T, E extends Throwable> void onSuccess(RetryContext context, RetryCallback<T, E> callback, T result) {
    }

		// 失败时回调
    /**
     * Called after every unsuccessful attempt at a retry.
     */
    default <T, E extends Throwable> void onError(RetryContext context, RetryCallback<T, E> callback,
          Throwable throwable) {
    }

}

这里仅讨论第一个 execute 方法的实现:

// 不可变类,线程安全类
public class RetryTemplate implements RetryOperations {
  // 略去 execute 语义外方法,如对象创建与初始化

  protected final Log logger = LogFactory.getLog(getClass());
  private volatile BackOffPolicy backOffPolicy = new NoBackOffPolicy();
  private volatile RetryPolicy retryPolicy = new SimpleRetryPolicy(3);
  private volatile RetryListener[] listeners = new RetryListener[0];
  private RetryContextCache retryContextCache = new MapRetryContextCache();
  private boolean throwLastExceptionOnExhausted;

  @Override
  public final <T, E extends Throwable> T execute(RetryCallback<T, E> retryCallback) throws E {
    return doExecute(retryCallback, null, null);
  }
  
	// 方法比较长,模版方法模式
  protected <T, E extends Throwable> T doExecute(RetryCallback<T, E> retryCallback,
                                                 RecoveryCallback<T> recoveryCallback, RetryState state) throws E, ExhaustedRetryException {
    RetryPolicy retryPolicy = this.retryPolicy;
    BackOffPolicy backOffPolicy = this.backOffPolicy;
    
    // Allow the retry policy to initialise itself...
    // 重试过程中,context 不断变化,每次重试需要初始化
    RetryContext context = open(retryPolicy, state);
    if (this.logger.isTraceEnabled()) {
      this.logger.trace("RetryContext retrieved: " + context);
    }
    
    // Make sure the context is available globally for clients who need
    // it...
    // 保证重试执行时可以随时获得 context,使用了 ThreadLocal, context 和线程绑定
    RetrySynchronizationManager.register(context);

    Throwable lastException = null;
    boolean exhausted = false;
    try {
      // 一些准备工作
      // 回调,可提前终止重试
      // Give clients a chance to enhance the context...
      boolean running = doOpenInterceptors(retryCallback, context);

      if (!running) {
        throw new TerminatedRetryException("Retry terminated abnormally by interceptor before first attempt");
      }
			// 设置 context 最大重试数
      if (!context.hasAttribute(RetryContext.MAX_ATTEMPTS)) {
        context.setAttribute(RetryContext.MAX_ATTEMPTS, retryPolicy.getMaxAttempts());
      }

      // Get or Start the backoff context...
      BackOffContext backOffContext = null;
      Object resource = context.getAttribute("backOffContext");
      if (resource instanceof BackOffContext) {
        backOffContext = (BackOffContext) resource;
      }
      if (backOffContext == null) {
        backOffContext = backOffPolicy.start(context);
        if (backOffContext != null) {
          context.setAttribute("backOffContext", backOffContext);
        }
      }
      Object label = retryCallback.getLabel();
      String labelMessage = (label != null) ? "; for: '" + label + "'" : "";

      // 准备工作结束,开始执行 retry 核心代码
      // 循环内部为任务执行的完整 try-catch 过程,基本思想和函数式基于轨道编程(Railway-Oriented-Programming)的 CompletableFuture 不同
      /*
      * We allow the whole loop to be skipped if the policy or context already
      * forbid the first try. This is used in the case of external retry to allow a
      * recovery in handleRetryExhausted without the callback processing (which
      * would throw an exception).
      */
      while (canRetry(retryPolicy, context) && !context.isExhaustedOnly()) {
        try {
          if (this.logger.isDebugEnabled()) {
            this.logger.debug("Retry: count=" + context.getRetryCount() + labelMessage);
          }
          // Reset the last exception, so if we are successful
          // the close interceptors will not think we failed...
          lastException = null;
          // 任务执行
          T result = retryCallback.doWithRetry(context);
          // 成功回调
          doOnSuccessInterceptors(retryCallback, context, result);
          return result;
        }
        catch (Throwable e) {
          lastException = e;
          try {
            // 每次异常回调
            // 进行的操作一般有:失败次数 + 1, 记录 lastException
            registerThrowable(retryPolicy, state, context, e);
          }
          catch (Exception ex) {
            throw new TerminatedRetryException("Could not register throwable", ex);
          }
          finally {
           	// RetryListener 失败回调
            doOnErrorInterceptors(retryCallback, context, e);
          }
          // 执行 backoff 策略
          if (canRetry(retryPolicy, context) && !context.isExhaustedOnly()) {
            try {
              backOffPolicy.backOff(backOffContext);
            }
            catch (BackOffInterruptedException ex) {
              // back off was prevented by another thread - fail the retry
              if (this.logger.isDebugEnabled()) {
                this.logger.debug("Abort retry because interrupted: count=" + context.getRetryCount()
                                  + labelMessage);
              }
              throw ex;
            }
          }
          
          if (this.logger.isDebugEnabled()) {
            this.logger.debug("Checking for rethrow: count=" + context.getRetryCount() + labelMessage);
          }

          if (shouldRethrow(retryPolicy, context, state)) {
            if (this.logger.isDebugEnabled()) {
              this.logger
                .debug("Rethrow in retry for policy: count=" + context.getRetryCount() + labelMessage);
            }
            throw RetryTemplate.<E>wrapIfNecessary(e);
          }
        } // while 循环内 try-catch 结束
			
        // 仅考虑无状态重试(state is null),可以忽略这段代码
        /*
        * A stateful attempt that can retry may rethrow the exception before now,
        * but if we get this far in a stateful retry there's a reason for it,
        * like a circuit breaker or a rollback classifier.
        */
        if (state != null && context.hasAttribute(GLOBAL_STATE)) {
          break;
        }
      } // while 循环末尾
      if (state == null && this.logger.isDebugEnabled()) {
        this.logger.debug("Retry failed last attempt: count=" + context.getRetryCount() + labelMessage);
      }
      exhausted = true;
      return handleRetryExhausted(recoveryCallback, context, state);
    }
    catch (Throwable e) {
      // 重试代码抛出异常,无法处理,rethrow
      throw RetryTemplate.<E>wrapIfNecessary(e);
    }
    finally {
      close(retryPolicy, context, state, lastException == null || exhausted);
      // RetryListener 关闭回调
      doCloseInterceptors(retryCallback, context, lastException);
      RetrySynchronizationManager.clear();
    }
  }
}

总结一下 Spring-Retry 的特点

  1. 支持回调(RetryListener) 和有状态上下文(RetryContext、backoffContext、RetryState)

  2. 缺点:不支持异步 backoff,backoff 在同一线程内。

  3. 上下文和线程绑定,底层使用 ThreadLocal,代码中会有隐式传参问题。

CompletableFuture 和重试机制有关的特点

  1. 若想实现特定返回值触发重试策略,CompletableFuture 存在成功运算管道和异常管道,推荐的做法是:thenCompose 转化某些错误值到特定异常,配置特定异常触发重试策略。

  2. ComletableFuture 中的结果为异常时,需要解包才能获取真实的代码执行时异常。

  3. CompletableFuture 提供了限时获取值方法,可以轻松实现超时终止策略。

  4. 取消机制,上文中的简易实现没有考虑 retry 方法返回结果被取消的情况,此时运行中的任务应该主动 cancel。

  5. 可以天然地支持异步重试(重试任务执行不限于同一线程中)

  6. 在单线程中sleep一段时间,再重试也是一种能接受的解决方案

CFFU

CFFU(CompletableFuture Fu )是一个小小的 CompletableFuture(CF)辅助增强库,提升 CF 使用体验并减少误用,在业务中更方便高效安全地使用 CF。
CFFU 并不支持重试,如果你想实现 CompletableFuture 的重试功能,可以使用 Resilience4J。

本文由博客一文多发平台 OpenWrite 发布!

posted @   桦说编程  阅读(75)  评论(0编辑  收藏  举报
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