Spring Cloud Hystrix原碼篇（十一）

童話述說我的結局發表於2021-01-02
SpringCloud

一、Hystrix處理流程

Hystrix流程圖如下：

 

 

 

Hystrix整個工作流如下：

  1. 構造一個 HystrixCommand或HystrixObservableCommand物件，用於封裝請求，並在構造方法配置請求被執行需要的引數；
  2. 執行命令，Hystrix提供了4種執行命令的方法，後面詳述；
  3. 判斷是否使用快取響應請求，若啟用了快取，且快取可用，直接使用快取響應請求。Hystrix支援請求快取，但需要使用者自定義啟動；
  4. 判斷熔斷器是否開啟，如果開啟，跳到第8步；
  5. 判斷執行緒池/佇列/訊號量是否已滿，已滿則跳到第8步；
  6. 執行HystrixObservableCommand.construct()或HystrixCommand.run()，如果執行失敗或者超時，跳到第8步；否則，跳到第9步；
  7. 統計熔斷器監控指標；
  8. 走Fallback備用邏輯
  9. 返回請求響應

從流程圖上可知道，第5步執行緒池/佇列/訊號量已滿時，還會執行第7步邏輯，更新熔斷器統計資訊，而第6步無論成功與否，都會更新熔斷器統計資訊。

二、Hystrix的核心原理

hystrix在服務降級熔斷的過程中有幾個步驟他是必須要去完成的

  •  可配置化的降級策略（根據不同的服務降級型別配置不同的降級策略方案）:
    • 三種方式：訊號量/執行緒 、超時（預設1s）、熔斷（錯誤率）
    • 在HystrixCommandProperty類中通過相關屬性去配置改變他的預設策略（上篇中有說明過）
  • 可以識別的降級邊界：
    • @HystrixCommand(Spring AOP通過註解標註一個介面的資源，去表示說明這個介面需要通過Hystrix來接管這個請求，如果達到註解內的配置要求就熔斷)
    • 自己去繼承HystrixCommand 抽象類，等下演示下，這玩意還挺好玩的
  • 資料採集：
    • 如何觸發熔斷（上篇幅也說過10s 內20個請求 ，錯誤率達到50），這裡引出的問題是如何採集資料，如何統計資料.
    • SEMAPHORE，最大併發數量 （它底層其實就是個AQS 統計次數tryAcquire(), acquire()）
  • 行為干預： 觸發降級/熔斷之後，對正常業務產生影響
  • 結果乾預： 通過fallback()返回資料
  • 自動恢復（處於熔斷狀態下，會每隔5s嘗試去恢復）

 2.1、通過HystrixCommand 接管我們定義的請求

上一篇幅我是通過註解的方式來進行服務熔錯的，這次不通過註解換一種方式，首先在spring-cloud-user服務中寫以下內容

 

 

 

 

 

 然後啟動服務訪問瀏覽器，結果如果我想的一樣

 

 

 2.2、Hystrix是如何工作的

下面演示個帶超時降級的Hystrix註解

 

 然後用AOP寫自己的攔截規則

 

 

/**
 *這裡面用到的是AOP的知識點，如果不瞭解可以先自行補下，後面我有空把Spring的AOP原理也寫下，這樣回頭看這個就沒這麼難了
 */
@Component
@Aspect  //切入
public class GhyHystrixAspect {
    //通過執行緒池去請求
    ExecutorService executorService= Executors.newFixedThreadPool(10);
    //定義切點針對GhyHystrix進行切入
    @Pointcut(value = "@annotation(GhyHystrix)")
    public void pointCut(){}
    //切入後執行的方法
    @Around(value = "pointCut()&&@annotation(hystrixCommand)")
    public Object doPointCut(ProceedingJoinPoint joinPoint, GhyHystrix hystrixCommand) throws InterruptedException, ExecutionException, TimeoutException, NoSuchMethodException, InvocationTargetException, IllegalAccessException {
        //定義超時降級
        int timeout=hystrixCommand.timeout();
        //前置的判斷邏輯
        Future future=executorService.submit(()->{
            try {
                return joinPoint.proceed(); //執行目標方法
            } catch (Throwable throwable) {
                throwable.printStackTrace();
            }
            return null;
        });
        Object result;
        try {
            //得到開始和結束時間判斷是否超時，如果超時就降級
            result=future.get(timeout, TimeUnit.MILLISECONDS);
        } catch (InterruptedException | ExecutionException | TimeoutException e) {
            e.printStackTrace();
            //超時了就取消請求
            future.cancel(true);
            // 先判斷是否為空如果空就把異常丟擲去
            if(StringUtils.isBlank(hystrixCommand.fallback())){
                throw e;
            }
            //呼叫fallback
            result=invokeFallback(joinPoint,hystrixCommand.fallback());
        }
        return result;
    }
   //反射呼叫
    private Object invokeFallback(ProceedingJoinPoint joinPoint,String fallback) throws NoSuchMethodException, InvocationTargetException, IllegalAccessException {
        MethodSignature signature=(MethodSignature)joinPoint.getSignature();
        //拿到方法的資訊
        Method method=signature.getMethod();
        //得到引數型別
        Class<?>[] parameterTypes=method.getParameterTypes();
        //以上是獲取被代理的方法的引數和Method
        //得到fallback方法
        try {
            Method fallbackMethod=joinPoint.getTarget().getClass().getMethod(fallback,parameterTypes);
            fallbackMethod.setAccessible(true);
            //完成反射呼叫
            return fallbackMethod.invoke(joinPoint.getTarget(),joinPoint.getArgs());
        } catch (Exception e) {
            e.printStackTrace();
            throw e;
        }
    }
}

然後再寫個呼叫邏輯，用自己定義的註解

 

 瀏覽器訪問，返回的不是我們剛剛定義的降級內容，其實這也挺好想的，我用的是之前的專案，之前在spring-cloud-api工程中定義了熔斷規則，改一下就好

 

 

 將這此內容改下就好，還有配置檔案隱藏下，這裡就不搞了

 三、Hystrix的熔斷的原理以及請求代理的原理

當請求過來時，如果請求失敗，先判斷請求次數是否達到了最小請求次數，再判斷錯誤率是否達到了閾值，如果沒達到就繼續請求，這個錯誤率的統計時間預設是10S；如果達到了閾值就要開啟斷路器，開啟斷 路器後有5秒的時間是熔斷狀態，5秒後，如果有請求過來，就會試著把請求傳送到遠端服務，如果成功，斷路器就關閉；如果失敗斷路器繼續開啟；這個流程就引出第一個概念，那就是滑動視窗

3.1、滑動視窗

在 hystrix 裡，大量使用了 RxJava 這個響應式函式程式設計框架，滑動視窗的實現也是使用了 RxJava 框架。它其實就是一個 流量控制技術；竟然提到了滑動視窗，那就必須要提兩上東西，一個是計數器，另一個就是滑動視窗;為了更通俗的理解計數器和滑動視窗關係，就以一個例子說明；假如有一個場景：要做一個請求限制，限制要求一分鐘內最多隻能有60個請求通過，這時最通用的做方就是用個計數器，計數一分鐘內請求的次數，在這一分鐘內每來一個請求計數器就加1；一分鐘過後進入下一個一分鐘時計數器就把計數歸零重新計數；所以說如果要限流判斷就只用判斷這一分鐘內的計數量就可以了，但這種做法在每個1分鐘的臨界值時是有問題的，問題是啥呢，假如說在0到58S時都沒有請求，但是突然在第59S時一下子來了60個請求，在60S時再來60個請求，這個時候發生的情況是在相鄰兩秒內一下子來了120個請求，此時因為59S在第一個時間段；60S在第二個時間段，所以沒有滿足觸發熔斷條件，這就導至了相鄰兩秒間的請求量過了閾值，系統很可能炸了，為此引出了另一個玩意，那就是滑動視窗；滑動視窗把一分鐘分成6個視窗，每個視窗是10S，紅色框代表可以滑動的滑動視窗，黑色的視窗代表10S的統計數值，第一個10S統計 完成後紅色滑動視窗會向前滑動一格，改成滑動視窗後他統計的就是紅色滑動視窗內的訪問量總和了

 

hystrix是通過滑動視窗統計的，他一共有10個視窗，每個視窗代表1S，所以他統計的是他10S內的資料

 

 

 

上圖的每個小矩形代表一個桶，可以看到，每個桶都記錄著1秒內的四個指標資料：成功量、失敗量、超時量和拒絕量，這裡的拒絕量指的就是上面流程圖中【訊號量/執行緒池資源檢查】中被拒絕的流量。10個桶合起來是一個完整的滑動視窗，所以計算一個滑動視窗的總資料需要將10個桶的資料加起來。

 

 四、Hystrix熔斷的原始碼分析

Hystrix熔斷的@HystrixCommand註解，是通過HystrixCommandAspect這個切面來處理的。其中關注@Around註解宣告的方法，它針對於請求合併，以及降級的註解進行代理。這裡重點針對HystrixCommand這個註解進行詳細分析。

  • getMethodFromTarget 獲取目標方法資訊
  • MetaHolder metaHolder = metaHolderFactory.create(joinPoint); 獲取後設資料，比如呼叫方法，HystrixProperty註解資料、方法引數等
  • HystrixCommandFactory.getInstance().create 獲取呼叫者，它持有一個命令物件，並且可以在合適的時候通過這個命令物件完成具體的業務邏輯
  • execute，執行命令
@Around("hystrixCommandAnnotationPointcut() ||
hystrixCollapserAnnotationPointcut()")
public Object methodsAnnotatedWithHystrixCommand(final ProceedingJoinPoint
joinPoint) throws Throwable {
  Method method = getMethodFromTarget(joinPoint);
  //省略程式碼...
  MetaHolderFactory metaHolderFactory =
META_HOLDER_FACTORY_MAP.get(HystrixPointcutType.of(method));
  MetaHolder metaHolder = metaHolderFactory.create(joinPoint);
  //如果是非同步，則建立GenericObservableCommand， 否則，則建立GenericCommand
  HystrixInvokable invokable =
HystrixCommandFactory.getInstance().create(metaHolder);
 
  ExecutionType executionType = metaHolder.isCollapserAnnotationPresent() ?
    metaHolder.getCollapserExecutionType() : metaHolder.getExecutionType();
  Object result;
  try {
    if (!metaHolder.isObservable()) { //是否是響應式的（由於我們這些都是同步的會走
這個邏輯）
     //預設是走這裡面，用命令執行器去執行
      result = CommandExecutor.execute(invokable, executionType,
metaHolder);
   } else {
      result = executeObservable(invokable, executionType, metaHolder);
   }
 } catch (HystrixBadRequestException e) {
    throw e.getCause();
 } catch (HystrixRuntimeException e) {
    throw hystrixRuntimeExceptionToThrowable(metaHolder, e);
}
  return result;
}

點選進入 CommandExecutor類的execute方法，這個方法主要用來執行命令，從程式碼中可以看出這裡有三個執行型別，分別是同步、非同步、以及響應式。其中，響應式又分為Cold Observable（observable.toObservable()） 和 HotObservable（observable.observe()）

預設的executionType=SYNCHRONOUS ，同步請求。

  • execute():同步執行，返回一個單一的物件結果，發生錯誤時丟擲異常。
  • queue():非同步執行，返回一個 Future 物件，包含著執行結束後返回的單一結果。
  • observe():這個方法返回一個 Observable 物件，它代表操作的多個結果，但是已經被訂閱者消費掉了。
  • toObservable():這個方法返回一個 Observable 物件，它代表操作的多個結果，需要我們們自己手動訂閱並消費掉。

需要注意的是，Hystrix用到了RxJava這個框架，它是一個響應式程式設計框架，在Android裡面用得比較多 

    public static Object execute(HystrixInvokable invokable, ExecutionType executionType, MetaHolder metaHolder) throws RuntimeException {
        Validate.notNull(invokable);
        Validate.notNull(metaHolder);
         
        switch (executionType) {

            case SYNCHRONOUS: {
                return castToExecutable(invokable, executionType).execute();
            }
            case ASYNCHRONOUS: {
                HystrixExecutable executable = castToExecutable(invokable, executionType);
                if (metaHolder.hasFallbackMethodCommand()
                        && ExecutionType.ASYNCHRONOUS == metaHolder.getFallbackExecutionType()) {
                    return new FutureDecorator(executable.queue());
                }
                return executable.queue();
            }
            case OBSERVABLE: {
                HystrixObservable observable = castToObservable(invokable);
                return ObservableExecutionMode.EAGER == metaHolder.getObservableExecutionMode() ? observable.observe() : observable.toObservable();
            }
            default:
                throw new RuntimeException("unsupported execution type: " + executionType);
        }
    }

因為是走預設的，所以進入HystrixCommand類的execute()方法；這個方法中，首先呼叫queue()，這個方法會返回一個future物件。

  public R execute() {
        try {
            return queue().get();
        } catch (Exception e) {
            throw Exceptions.sneakyThrow(decomposeException(e));
        }
    }

queue這個方法中，返回了一個Future物件，這個future物件的實現是f，f是以匿名內部類，它是Java.util.concurrent中定一個的一個非同步帶返回值物件。當呼叫queue().get()方法時，最終是委派給了delegate.get 方法。

public Future<R> queue() {
  /*
    * The Future returned by Observable.toBlocking().toFuture() does not
implement the
    * interruption of the execution thread when the "mayInterrupt" flag of
Future.cancel(boolean) is set to true;
    * thus, to comply with the contract of Future, we must wrap around it.
    */
  final Future<R> delegate = toObservable().toBlocking().toFuture();
  final Future<R> f = new Future<R>() {
    @Override
    public boolean cancel(boolean mayInterruptIfRunning) {
      if (delegate.isCancelled()) {
        return false;
     }
      if
(HystrixCommand.this.getProperties().executionIsolationThreadInterruptOnFutureCa
ncel().get()) {
        /*
          * The only valid transition here is false -> true. If there
are two futures, say f1 and f2, created by this command
          * (which is super-weird, but has never been prohibited),
and calls to f1.cancel(true) and to f2.cancel(false) are
          * issued by different threads, it's unclear about what
value would be used by the time mayInterruptOnCancel is checked.
          * The most consistent way to deal with this scenario is to
say that if *any* cancellation is invoked with interruption,
          * than that interruption request cannot be taken back.
          */
        interruptOnFutureCancel.compareAndSet(false,
mayInterruptIfRunning);
     }
      final boolean res = delegate.cancel(interruptOnFutureCancel.get());
      if (!isExecutionComplete() && interruptOnFutureCancel.get()) {
        final Thread t = executionThread.get();
        if (t != null && !t.equals(Thread.currentThread())) {
t.interrupt();
       }
     }
      return res;
   }
    @Override
    public boolean isCancelled() {
      return delegate.isCancelled();
   }
    @Override
    public boolean isDone() {
      return delegate.isDone();
   }
    //最終會呼叫此方法
    @Override
    public R get() throws InterruptedException, ExecutionException {
      return delegate.get();
   }
    @Override
    public R get(long timeout, TimeUnit unit) throws InterruptedException,
ExecutionException, TimeoutException {
      return delegate.get(timeout, unit);
   }
 };
  /* special handling of error states that throw immediately */
  if (f.isDone()) {
    try {
      f.get();
      return f;
   } catch (Exception e) {
      Throwable t = decomposeException(e);
      if (t instanceof HystrixBadRequestException) {
        return f;
     } else if (t instanceof HystrixRuntimeException) {
        HystrixRuntimeException hre = (HystrixRuntimeException) t;
        switch (hre.getFailureType()) {
          case COMMAND_EXCEPTION:
          case TIMEOUT:
            // we don't throw these types from queue() only from
queue().get() as they are execution errors
            return f;
          default:
            // these are errors we throw from queue() as they as
rejection type errors
            throw hre;
       }
     } else {
        throw Exceptions.sneakyThrow(t);
     }
   }
 }
return f;
}

因為最終是委派給了delegate.get 方法執行，而delegate在開頭final Future<R> delegate = toObservable().toBlocking().toFuture();中，所以進入toObservable()方法中，在RxJava中，分為幾種角色

  • Observable（被觀察者），它的主要作用是產生事件
  • Observer（觀察者），它的作用是接收事件並作出相應
  • Subscribe（訂閱），它用來連線被觀察者和觀察者
  • Event（事件），被觀察者、觀察者、溝通的載體

在queue中，呼叫toObservable()方法建立一個被觀察者。通過Observable定義一個被觀察者，這個被觀察者會被toObservable().toBlocking().toFuture() ，實際上就是返回可獲得 run() 抽象方法執行結果的Future 。 run() 方法由子類實現，執行正常的業務邏輯。在下面這段程式碼中，當存在subscriber時，便會呼叫Func0#call() 方法，而這個subscriber是在 toBlocking() 中被訂閱的。

  • 呼叫 isRequestCachingEnabled(); 判斷請求結果快取功能是否開啟，如果開啟並且命中了快取，則會以Observable形式返回一個快取結果
  • 建立執行命令的Observable： hystrixObservable
  • 當快取處於開啟狀態並且沒有命中快取時，則建立一個“訂閱了執行命令的Observable”：HystrixCommandResponseFromCache
    • 建立儲存到快取的Observable： HystrixCachedObservable
    • 將toCache新增到快取中，返回獲取快取的Observable：fromCache
    • 如果新增失敗: fromCache!=null, 則呼叫 toCache.unsubscribe() 方法，取消HystrixCachedObservable 的訂閱
    • 如果新增成功，則呼叫 toCache.toObservable(); 獲得快取Observable
  • 當快取特性沒有開啟時，則返回執行命令的Observable。
   public Observable<R> toObservable() {
        final AbstractCommand<R> _cmd = this;

        //doOnCompleted handler already did all of the SUCCESS work
        //doOnError handler already did all of the FAILURE/TIMEOUT/REJECTION/BAD_REQUEST work
        final Action0 terminateCommandCleanup = new Action0() {

            @Override
            public void call() {
                if (_cmd.commandState.compareAndSet(CommandState.OBSERVABLE_CHAIN_CREATED, CommandState.TERMINAL)) {
                    handleCommandEnd(false); //user code never ran
                } else if (_cmd.commandState.compareAndSet(CommandState.USER_CODE_EXECUTED, CommandState.TERMINAL)) {
                    handleCommandEnd(true); //user code did run
                }
            }
        };

        //mark the command as CANCELLED and store the latency (in addition to standard cleanup)
        final Action0 unsubscribeCommandCleanup = new Action0() {
            @Override
            public void call() {
                if (_cmd.commandState.compareAndSet(CommandState.OBSERVABLE_CHAIN_CREATED, CommandState.UNSUBSCRIBED)) {
                    if (!_cmd.executionResult.containsTerminalEvent()) {
                        _cmd.eventNotifier.markEvent(HystrixEventType.CANCELLED, _cmd.commandKey);
                        try {
                            executionHook.onUnsubscribe(_cmd);
                        } catch (Throwable hookEx) {
                            logger.warn("Error calling HystrixCommandExecutionHook.onUnsubscribe", hookEx);
                        }
                        _cmd.executionResultAtTimeOfCancellation = _cmd.executionResult
                                .addEvent((int) (System.currentTimeMillis() - _cmd.commandStartTimestamp), HystrixEventType.CANCELLED);
                    }
                    handleCommandEnd(false); //user code never ran
                } else if (_cmd.commandState.compareAndSet(CommandState.USER_CODE_EXECUTED, CommandState.UNSUBSCRIBED)) {
                    if (!_cmd.executionResult.containsTerminalEvent()) {
                        _cmd.eventNotifier.markEvent(HystrixEventType.CANCELLED, _cmd.commandKey);
                        try {
                            executionHook.onUnsubscribe(_cmd);
                        } catch (Throwable hookEx) {
                            logger.warn("Error calling HystrixCommandExecutionHook.onUnsubscribe", hookEx);
                        }
                        _cmd.executionResultAtTimeOfCancellation = _cmd.executionResult
                                .addEvent((int) (System.currentTimeMillis() - _cmd.commandStartTimestamp), HystrixEventType.CANCELLED);
                    }
                    handleCommandEnd(true); //user code did run
                }
            }
        };

        final Func0<Observable<R>> applyHystrixSemantics = new Func0<Observable<R>>() {
            @Override
            public Observable<R> call() {
                if (commandState.get().equals(CommandState.UNSUBSCRIBED)) {
                    return Observable.never();
                }
                return applyHystrixSemantics(_cmd);
            }
        };

        final Func1<R, R> wrapWithAllOnNextHooks = new Func1<R, R>() {
            @Override
            public R call(R r) {
                R afterFirstApplication = r;

                try {
                    afterFirstApplication = executionHook.onComplete(_cmd, r);
                } catch (Throwable hookEx) {
                    logger.warn("Error calling HystrixCommandExecutionHook.onComplete", hookEx);
                }

                try {
                    return executionHook.onEmit(_cmd, afterFirstApplication);
                } catch (Throwable hookEx) {
                    logger.warn("Error calling HystrixCommandExecutionHook.onEmit", hookEx);
                    return afterFirstApplication;
                }
            }
        };

        final Action0 fireOnCompletedHook = new Action0() {
            @Override
            public void call() {
                try {
                    executionHook.onSuccess(_cmd);
                } catch (Throwable hookEx) {
                    logger.warn("Error calling HystrixCommandExecutionHook.onSuccess", hookEx);
                }
            }
        };
return Observable.defer(new Func0<Observable<R>>() {
  @Override
  public Observable<R> call() {
    /* this is a stateful object so can only be used once */
    /* CAS保證命令只執行一次 */
    if (!commandState.compareAndSet(CommandState.NOT_STARTED,
CommandState.OBSERVABLE_CHAIN_CREATED)) {
      IllegalStateException ex = new IllegalStateException("This instance
can only be executed once. Please instantiate a new instance.");
      //TODO make a new error type for this
      throw new HystrixRuntimeException(FailureType.BAD_REQUEST_EXCEPTION,
_cmd.getClass(), getLogMessagePrefix() + " command executed multiple times -
this is not permitted.", ex, null);
   }
   // 命令開始時間戳
    commandStartTimestamp = System.currentTimeMillis();
    // 列印日誌
    if (properties.requestLogEnabled().get()) {
      // log this command execution regardless of what happened
      if (currentRequestLog != null) {
currentRequestLog.addExecutedCommand(_cmd);
     }
   }
   // 快取開關，快取KEY（這個是Hystrix中請求快取功能，hystrix支援將一個請求結果快取起
來，下一個具有相同key的請求將直接從快取中取出結果，減少請求開銷）
    final boolean requestCacheEnabled = isRequestCachingEnabled();
    final String cacheKey = getCacheKey();
    /* try from cache first */
    if (requestCacheEnabled) {//如果開啟了快取機制，則從快取中獲取結果
      HystrixCommandResponseFromCache<R> fromCache =
(HystrixCommandResponseFromCache<R>) requestCache.get(cacheKey);
      if (fromCache != null) {
        isResponseFromCache = true;
        return handleRequestCacheHitAndEmitValues(fromCache, _cmd);
     }
   }
    // 宣告執行命令的Observable
    Observable<R> hystrixObservable =
      Observable.defer(applyHystrixSemantics)
     .map(wrapWithAllOnNextHooks);
    Observable<R> afterCache;
    //儲存請求結果到快取中
    if (requestCacheEnabled && cacheKey != null) {
      // wrap it for caching
      HystrixCachedObservable<R> toCache =
HystrixCachedObservable.from(hystrixObservable, _cmd);
      HystrixCommandResponseFromCache<R> fromCache =
(HystrixCommandResponseFromCache<R>) requestCache.putIfAbsent(cacheKey,
toCache);
      if (fromCache != null) {
        // another thread beat us so we'll use the cached value instead
        toCache.unsubscribe();
        isResponseFromCache = true;
        return handleRequestCacheHitAndEmitValues(fromCache, _cmd);
     } else {
        // we just created an ObservableCommand so we cast and return it
        afterCache = toCache.toObservable();
     }
   } else {
      afterCache = hystrixObservable;
   }
    return afterCache
     .doOnTerminate(terminateCommandCleanup)   // perform cleanup once
(either on normal terminal state (this line), or unsubscribe (next line))
     .doOnUnsubscribe(unsubscribeCommandCleanup) // perform cleanup once
     .doOnCompleted(fireOnCompletedHook);
 }
});

執行命令的Observable的定義如下，通過defer定義了一個 applyHystrixSemantics 的事件。

final Func0<Observable<R>> applyHystrixSemantics = new Func0<Observable<R>>() {
  @Override
 public Observable<R> call() {
    // 當commandState處於UNSUBSCRIBED時，不執行命令
    if (commandState.get().equals(CommandState.UNSUBSCRIBED)) {
      return Observable.never();
   }
    //返回執行命令的Observable
    return applyHystrixSemantics(_cmd);
 }
};
Observable<R> hystrixObservable =
  Observable.defer(applyHystrixSemantics)
 .map(wrapWithAllOnNextHooks);

applyHystrixSemantics方法；假設快取特性未開啟或者未命中快取，那麼程式碼將執行 applyHystrixSemantics 。

  • 傳入的_cmd是一個GenericCommand，最終執行這個command中的run方法，本質就是完成對queryOrder方法的代理
  • circuitBreaker.allowRequest() 如果為true，表示當前不處於熔斷狀態，正常執行，否則，呼叫 handleShortCircuitViaFallback 實現服務降級，如果我們配置了fallback方法，則會獲得我們配置的fallback執行
  • 如果當前hystrix處於未熔斷狀態，則
    • getExecutionSemaphore 判斷當前策略是否為訊號量（TryableSemaphoreNoOp/TryableSemaphoreActual），如果是，則呼叫 tryAcquire 來獲取訊號量。如果當前訊號量滿了，則呼叫 handleSemaphoreRejectionViaFallback 方法。
    • 呼叫 executeCommandAndObserve 獲取命令執行Observable。

 

   private Observable<R> applyHystrixSemantics(final AbstractCommand<R> _cmd) {
        // mark that we're starting execution on the ExecutionHook
        // if this hook throws an exception, then a fast-fail occurs with no fallback.  No state is left inconsistent
        executionHook.onStart(_cmd);

        /* determine if we're allowed to execute */
        if (circuitBreaker.allowRequest()) {
            final TryableSemaphore executionSemaphore = getExecutionSemaphore();
            final AtomicBoolean semaphoreHasBeenReleased = new AtomicBoolean(false);
            final Action0 singleSemaphoreRelease = new Action0() {
                @Override
                public void call() {
                    if (semaphoreHasBeenReleased.compareAndSet(false, true)) {
                        executionSemaphore.release();
                    }
                }
            };

            final Action1<Throwable> markExceptionThrown = new Action1<Throwable>() {
                @Override
                public void call(Throwable t) {
                    eventNotifier.markEvent(HystrixEventType.EXCEPTION_THROWN, commandKey);
                }
            };

            if (executionSemaphore.tryAcquire()) {
                try {
                    /* used to track userThreadExecutionTime */
                    executionResult = executionResult.setInvocationStartTime(System.currentTimeMillis());
                   //跟進
                    return executeCommandAndObserve(_cmd)
                            .doOnError(markExceptionThrown)
                            .doOnTerminate(singleSemaphoreRelease)
                            .doOnUnsubscribe(singleSemaphoreRelease);
                } catch (RuntimeException e) {
                    return Observable.error(e);
                }
            } else {
                return handleSemaphoreRejectionViaFallback();
            }
        } else {
            return handleShortCircuitViaFallback();
        }
    }

executeCommandAndObserve

  • 定義不同的回撥，doOnNext、doOnCompleted、onErrorResumeNext、doOnEach。
  • 呼叫executeCommandWithSpecifiedIsolation獲得執行命令的Observable
  • 若執行命令超時特性開啟，呼叫 Observable.lift 方法實現執行命令超時功能。
private Observable<R> executeCommandAndObserve(final AbstractCommand<R> _cmd) {
  final HystrixRequestContext currentRequestContext =
HystrixRequestContext.getContextForCurrentThread();
  //Action和Func都是定義的一個動作，Action是無返回值，Func是有返回值
  // doOnNext中的回撥。即命令執行之前執行的操作
  final Action1<R> markEmits //...
// doOnCompleted中的回撥。命令執行完畢後執行的操作
  final Action0 markOnCompleted = //...
// onErrorResumeNext中的回撥。命令執行失敗後的回退邏輯
  final Func1<Throwable, Observable<R>> handleFallback = //...
// doOnEach中的回撥。`Observable`每發射一個資料都會執行這個回撥，設定請求上下文
  final Action1<Notification<? super R>> setRequestContext =//...
  Observable<R> execution;
  if (properties.executionTimeoutEnabled().get()) {
    execution = executeCommandWithSpecifiedIsolation(_cmd)
      .lift(new HystrixObservableTimeoutOperator<R>(_cmd));
  } else {
    execution = executeCommandWithSpecifiedIsolation(_cmd);
  }
  return execution.doOnNext(markEmits)
.doOnCompleted(markOnCompleted)
    .onErrorResumeNext(handleFallback)
    .doOnEach(setRequestContext);
}

executeCommandWithSpecifiedIsolation方法，這個方法首先是根據當前不同的資源隔離策略執行不同的邏輯，THREAD、SEMAPHORE，這裡就不展開實現細節，我們直接看執行的方法 getUserExecutionObservable 。

private Observable<R> executeCommandWithSpecifiedIsolation(final
AbstractCommand<R> _cmd) {
  if (properties.executionIsolationStrategy().get() ==
ExecutionIsolationStrategy.THREAD) {
    // mark that we are executing in a thread (even if we end up being
rejected we still were a THREAD execution and not SEMAPHORE)
    return Observable.defer(new Func0<Observable<R>>() {
      @Override
      public Observable<R> call() {
        executionResult = executionResult.setExecutionOccurred();
        if
(!commandState.compareAndSet(CommandState.OBSERVABLE_CHAIN_CREATED,
CommandState.USER_CODE_EXECUTED)) {
          return Observable.error(new IllegalStateException("execution
attempted while in state : " + commandState.get().name()));
       }
        metrics.markCommandStart(commandKey, threadPoolKey,
ExecutionIsolationStrategy.THREAD);
        if (isCommandTimedOut.get() == TimedOutStatus.TIMED_OUT) {
          // the command timed out in the wrapping thread so we will
return immediately
          // and not increment any of the counters below or other such
logic
          return Observable.error(new RuntimeException("timed out
before executing run()"));
       }
        if (threadState.compareAndSet(ThreadState.NOT_USING_THREAD,
ThreadState.STARTED)) {
          //we have not been unsubscribed, so should proceed
          HystrixCounters.incrementGlobalConcurrentThreads();
          threadPool.markThreadExecution();
          // store the command that is being run
          endCurrentThreadExecutingCommand =
Hystrix.startCurrentThreadExecutingCommand(getCommandKey());
          executionResult = executionResult.setExecutedInThread();
          /**
            * If any of these hooks throw an exception, then it
appears as if the actual execution threw an error
            */
          try {
            executionHook.onThreadStart(_cmd);
            executionHook.onRunStart(_cmd);
            executionHook.onExecutionStart(_cmd);
            return getUserExecutionObservable(_cmd);
} catch (Throwable ex) {
            return Observable.error(ex);
         }
       } else {
          //command has already been unsubscribed, so return
immediately
          return Observable.error(new RuntimeException("unsubscribed
before executing run()"));
       }
     }
   }).doOnTerminate(new Action0() {
      @Override
      public void call() {
        if (threadState.compareAndSet(ThreadState.STARTED,
ThreadState.TERMINAL)) {
          handleThreadEnd(_cmd);
       }
        if (threadState.compareAndSet(ThreadState.NOT_USING_THREAD,
ThreadState.TERMINAL)) {
          //if it was never started and received terminal, then no
need to clean up (I don't think this is possible)
       }
        //if it was unsubscribed, then other cleanup handled it
     }
   }).doOnUnsubscribe(new Action0() {
      @Override
      public void call() {
        if (threadState.compareAndSet(ThreadState.STARTED,
ThreadState.UNSUBSCRIBED)) {
          handleThreadEnd(_cmd);
       }
        if (threadState.compareAndSet(ThreadState.NOT_USING_THREAD,
ThreadState.UNSUBSCRIBED)) {
          //if it was never started and was cancelled, then no need to
clean up
       }
        //if it was terminal, then other cleanup handled it
     }
   }).subscribeOn(threadPool.getScheduler(new Func0<Boolean>() {
      @Override
      public Boolean call() {
        return
properties.executionIsolationThreadInterruptOnTimeout().get() &&
_cmd.isCommandTimedOut.get() == TimedOutStatus.TIMED_OUT;
     }
   }));
 } else {
    return Observable.defer(new Func0<Observable<R>>() {
      @Override
      public Observable<R> call() {
        executionResult = executionResult.setExecutionOccurred();
        if
(!commandState.compareAndSet(CommandState.OBSERVABLE_CHAIN_CREATED,
CommandState.USER_CODE_EXECUTED)) {
          return Observable.error(new IllegalStateException("execution
attempted while in state : " + commandState.get().name()));
       }
metrics.markCommandStart(commandKey, threadPoolKey,
ExecutionIsolationStrategy.SEMAPHORE);
        // semaphore isolated
        // store the command that is being run
        endCurrentThreadExecutingCommand =
Hystrix.startCurrentThreadExecutingCommand(getCommandKey());
        try {
          executionHook.onRunStart(_cmd);
          executionHook.onExecutionStart(_cmd);
          return getUserExecutionObservable(_cmd);  //the
getUserExecutionObservable method already wraps sync exceptions, so this
shouldn't throw
       } catch (Throwable ex) {
          //If the above hooks throw, then use that as the result of
the run method
          return Observable.error(ex);
       }
     }
   });
 }
}

 

呼叫 getExecutionObservable 方法建立 命令執行Observable 。 getExecutionObservable 方法是個抽象方法， HystrixCommand 實現了該方法。

 

private Observable<R> getUserExecutionObservable(final AbstractCommand<R> _cmd)
{
  Observable<R> userObservable;
  try {
    userObservable = getExecutionObservable();
 } catch (Throwable ex) {
    // the run() method is a user provided implementation so can throw
instead of using Observable.onError
    // so we catch it here and turn it into Observable.error
    userObservable = Observable.error(ex);
 }
  return userObservable
   .lift(new ExecutionHookApplication(_cmd))
   .lift(new DeprecatedOnRunHookApplication(_cmd));
}

 

呼叫 HystrixCommand.getExecutionObservable 方法建立命令執行Observable這裡最終呼叫的是run方法，通過Observable.just， just是RxJava中的一個操作符，它可以接受一個或者多個引數來建立一個Observable物件。而這個run（）方法是一個抽象方法，在HystrixCommand中並沒有實現，而是在子類中實現，而此時傳遞的cmd=GenricCommand正好實現了HystrixCommand，重寫了run方法。

@Override
final protected Observable<R> getExecutionObservable() {
  return Observable.defer(new Func0<Observable<R>>() {
    @Override
    public Observable<R> call() {
      try {
        return Observable.just(run());
     } catch (Throwable ex) {
        return Observable.error(ex);
     }
   }
 }).doOnSubscribe(new Action0() {
    @Override
    public void call() {
      // Save thread on which we get subscribed so that we can interrupt
it later if needed
      executionThread.set(Thread.currentThread());
   }
 });
}

enericCommand類中的run方法，這裡的實現和前面自定義的 HystrixCommandService 實現是一樣的，同樣是整合HystrixCommand，重寫run方法。這裡也是如此。

  • 首先呼叫 getCommandAction() 方法獲取 CommandAction ，我們的示例中獲取到的是MethodExecutionAction 。
  • 然後呼叫 MethodExecutionAction.execute 方法，傳入 ExecutionType 引數，我們的示例中傳入的是 ExecutionType.SYNCHRONOUS 。
@Override
protected Object run() throws Exception {
  LOGGER.debug("execute command: {}", getCommandKey().name());
  return process(new Action() {
    @Override
    Object execute() {
      return getCommandAction().execute(getExecutionType());
   }
 });
}

 






 

 

 






 



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