先复习下Hystrix的整体流程
- 构造一个 HystrixCommand或HystrixObservableCommand对象，用于封装请求，并在构造方法配置请求被执行需要的参数；
- 执行命令，Hystrix提供了4种执行命令的方法
- 判断是否使用缓存响应请求，若启用了缓存，且缓存可用，直接使用缓存响应请求。Hystrix支持请求缓存，但需要用户自定义启动；
- 判断熔断器是否打开，如果打开，执行第8步；
- 判断线程池/队列/信号量是否已满，已满则执行第8步；
- 执行HystrixObservableCommand.construct()或HystrixCommand.run()，如果执行失败或者超时，执行第8步；否则，跳到第9步；
- 统计熔断器监控指标；
- 走Fallback备用逻辑
- 返回请求响应
一，execute方法分析
承接上篇，在HystrixCommandAspect这个切面里会创建HystrixInvokable对象，进而执行。
Object result;
try {
if (!metaHolder.isObservable()) {
result = CommandExecutor.execute(invokable, executionType, metaHolder);
} else {
result = executeObservable(invokable, executionType, metaHolder);
}
} catch (HystrixBadRequestException e) {
throw e.getCause() != null ? e.getCause() : e;
} catch (HystrixRuntimeException e) {
throw hystrixRuntimeExceptionToThrowable(metaHolder, e);
}这里就来分析下execute的流程。Hystrix是支持同步，异步，观察这个三个模式的，我们只看同步，调用链路是：HystrixCommand.execute() -> queue() -> toObservable()
public Observable<R> toObservable() {
.... 一些action的定义 ....
final Func0<Observable<R>> applyHystrixSemantics = new Func0<Observable<R>>() {
public Observable<R> call() {
if(this.commandState.get()).equals(AbstractCommand.CommandState.UNSUBSCRIBED)){
return Observable.never()
}else{
applyHystrixSemantics(AbstractCommand.this);
}
}
};
...
return Observable.defer(new Func0<Observable<R>>() {
public Observable<R> call() {
...判断是否开启缓存，对应上整体流程的3步...
boolean requestCacheEnabled = AbstractCommand.this.isRequestCachingEnabled();
String cacheKey = AbstractCommand.this.getCacheKey();
if (requestCacheEnabled) {
//拿去缓存，如果存在缓存的话，直接返回
HystrixCommandResponseFromCache<R> fromCache = (HystrixCommandResponseFromCache<R>) requestCache.get(cacheKey);
if (fromCache != null) {
isResponseFromCache = true;
return handleRequestCacheHitAndEmitValues(fromCache, _cmd);
}
}
Observable<R> hystrixObservable = Observable.defer(applyHystrixSemantics).map(wrapWithAllOnNextHooks);
Observable afterCache;
if (requestCacheEnabled && cacheKey != null) {
... 缓存后续的一些判断.....
} else {
afterCache = hystrixObservable;
}
return afterCache.doOnTerminate(terminateCommandCleanup)
.doOnUnsubscribe(unsubscribeCommandCleanup)
.doOnCompleted(fireOnCompletedHook);
}
});
}
call里面的方法主要用途：
- 判断一下是否开启了缓存，如果开启了就直接返回
- 没有开启或者还没有缓存的时候就执行Observable.defer(applyHystrixSemantics)，执行后返回。
熔断器关闭或打开的判断，这对应开头整体流程的第4步。
private Observable<R> applyHystrixSemantics(AbstractCommand<R> _cmd) {
this.executionHook.onStart(_cmd);
//判读是不是熔断了。
if (this.circuitBreaker.allowRequest()) {
/**
*如果使用的是信号量返回TryableSemaphoreActual，不是返回
*TryableSemaphoreNoOp,TryableSemaphoreNoOp.tryAcquire()永远都是返回true
*/
final TryableSemaphore executionSemaphore = getExecutionSemaphore();
。。。
//信号量的控制
if (executionSemaphore.tryAccaquire()) {
try {
this.executionResult = this.executionResult.setInvocationStartTime(System.currentTimeMillis());
//如果都成功的话会执行executeCommandAndObserve
return this.executeCommandAndObserve(_cmd)
.doOnError(markExceptionThrown)
.doOnTerminate(singleSemaphoreRelease)
.doOnUnsubscribe(singleSemaphoreRelease);
} catch (RuntimeException var7) {
return Observable.error(var7);
}
} else {
return this.handleSemaphoreRejectionViaFallback();
}
} else {//执行熔断后的逻辑
return this.handleShortCircuitViaFallback();
}
}
二，熔断器降级分析
接着分析this.circuitBreaker.allowRequest()
static class HystrixCircuitBreakerImpl implements HystrixCircuitBreaker {
private final HystrixCommandProperties properties;
private final HystrixCommandMetrics metrics;
//熔断器是否开启
/* track whether this circuit is open/closed at any given point in time (default to false==closed) */
private AtomicBoolean circuitOpen = new AtomicBoolean(false);
/* when the circuit was marked open or was last allowed to try a 'singleTest' */
private AtomicLong circuitOpenedOrLastTestedTime = new AtomicLong();
protected HystrixCircuitBreakerImpl(HystrixCommandKey key, HystrixCommandGroupKey commandGroup, HystrixCommandProperties properties, HystrixCommandMetrics metrics) {
this.properties = properties;
this.metrics = metrics;
}
//当半开半闭状态下，如果这次请求成功而了，则把熔断器设为false,且让统计指标reset
public void markSuccess() {
if (circuitOpen.get()) {
if (circuitOpen.compareAndSet(true, false)) {
//win the thread race to reset metrics
//Unsubscribe from the current stream to reset the health counts stream. This only affects the health counts view,
//and all other metric consumers are unaffected by the reset
metrics.resetStream();
}
}
}
@Override
public boolean allowRequest() {
//判断是否强制打开熔断器
if (properties.circuitBreakerForceOpen().get()) {
return false;
}
//是否强制关闭熔断器
if (properties.circuitBreakerForceClosed().get()) {
isOpen();
return true;
}
return !isOpen() || allowSingleTest();
}
public boolean allowSingleTest() {
long timeCircuitOpenedOrWasLastTested = circuitOpenedOrLastTestedTime.get();
// 1) if the circuit is open
// 2) and it's been longer than 'sleepWindow' since we opened the circuit
//熔断器是开启的，且当前时间比开启熔断器的时间加上sleepWindow时间还要长
if (circuitOpen.get() && System.currentTimeMillis() > timeCircuitOpenedOrWasLastTested + properties.circuitBreakerSleepWindowInMilliseconds().get()) {
// We push the 'circuitOpenedTime' ahead by 'sleepWindow' since we have allowed one request to try.
// If it succeeds the circuit will be closed, otherwise another singleTest will be allowed at the end of the 'sleepWindow'.
//设置当前时间到timeCircuitOpenedOrWasLastTested，
//如果半开半闭的状态下，如果这次请求成功了则会调用markSuccess，让熔断器状态设为false,
//如果不成功，就不需要了。
//案例：半开半合状态下，熔断开启时间为00:00:00,sleepWindow为10s，如果00:00:15秒的时候调用，如果调用失败，
//在00:00:15至00:00:25秒这个区间都是熔断的，
if (circuitOpenedOrLastTestedTime.compareAndSet(timeCircuitOpenedOrWasLastTested, System.currentTimeMillis())) {
// if this returns true that means we set the time so we'll return true to allow the singleTest
// if it returned false it means another thread raced us and allowed the singleTest before we did
return true;
}
}
return false;
}
@Override
public boolean isOpen() {
//判断是否熔断了，circuitOpen是熔断的状态 ，true为熔断，false为不熔断
if (circuitOpen.get()) {
return true;
}
//获取统计到的指标信息
HealthCounts health = metrics.getHealthCounts();
// 一个时间窗口(默认10s钟)总请求次数是否大于circuitBreakerRequestVolumeThreshold 默认为20s
if (health.getTotalRequests() < properties.circuitBreakerRequestVolumeThreshold().get()) {
return false;
}
// 错误率(总错误次数/总请求次数)小于circuitBreakerErrorThresholdPercentage(默认50%)
if (health.getErrorPercentage() < properties.circuitBreakerErrorThresholdPercentage().get()) {
return false;
} else {
// 反之，熔断状态将从CLOSED变为OPEN，且circuitOpened==>当前时间戳
if (circuitOpen.compareAndSet(false, true)) {
//并且把当前时间设置到circuitOpenedOrLastTestedTime，可待后面的时间的对比
circuitOpenedOrLastTestedTime.set(System.currentTimeMillis());
return true;
} else {
return true;
}
}
}
}
- 判断是否强制开启熔断器和强制关闭熔断器
- 先判断熔断是否开启，然后判断是否需要熔断，如果需要熔断则个性熔断状态并重置熔断时间为当前时间。熔断的条件是：
1)时间窗口内(默认10s钟)总请求次数大于20次
2)时间窗口内(默认10s钟)失败率大于50% - 熔断的情况下就执行allowSingleTest，让开启熔断的都能往下执行。可以执行的条件是：
1)circuitOpen.get() 为true，确保是普通的熔断，而不是强制熔断
2)当前时间比开启熔断器的时间加上sleepWindow时间还要长 - 在半开半必的状态下请求成功了，再调用markSuccess()方法，从而将熔断器关闭并重新统计各项指标
allowSingleTest返回true的简单的可以叫为半开半闭状态
三，信号量隔离的分析
这个对应整体流程里的第5步
/* package */static class TryableSemaphoreActual implements TryableSemaphore {
protected final HystrixProperty<Integer> numberOfPermits;
private final AtomicInteger count = new AtomicInteger(0);
public TryableSemaphoreActual(HystrixProperty<Integer> numberOfPermits) {
this.numberOfPermits = numberOfPermits;
}
@Override
public boolean tryAcquire() {
int currentCount = count.incrementAndGet();
if (currentCount > numberOfPermits.get()) {
count.decrementAndGet();
return false;
} else {
return true;
}
}
}
/* package */static class TryableSemaphoreNoOp implements TryableSemaphore {
public static final TryableSemaphore DEFAULT = new TryableSemaphoreNoOp();
@Override
public boolean tryAcquire() {
return true;
}
}
开启了信号量隔离,TryableSemaphoreActual会把信号量增加1，如果currentCount > numberOfPermits.get()的时候就返回false,信号量降级。
没有开启信号量隔离，TryableSemaphoreNoOp.tryAcquire()永远都是返回true。
如果没熔断，没使用信号量，则会往下执行executeCommandAndObserve。
private Observable<R> executeCommandAndObserve(final AbstractCommand<R> _cmd) {
final HystrixRequestContext currentRequestContext = HystrixRequestContext.getContextForCurrentThread();
....
Observable<R> execution;
//判断是否超时隔离
if (properties.executionTimeoutEnabled().get()) {
execution = executeCommandWithSpecifiedIsolation(_cmd)
.lift(new HystrixObservableTimeoutOperator<R>(_cmd));
} else {
execution = executeCommandWithSpecifiedIsolation(_cmd);
}
//markEmits,markOnCompleted,handleFallback,setRequestContext都是匿名内部类，都在这个方法里定义了，
return execution.doOnNext(markEmits)
.doOnCompleted(markOnCompleted)
.onErrorResumeNext(handleFallback)
.doOnEach(setRequestContext);
}
四，超时隔离分析
private static class HystrixObservableTimeoutOperator<R> implements Operator<R, R> {
final AbstractCommand<R> originalCommand;
public HystrixObservableTimeoutOperator(final AbstractCommand<R> originalCommand) {
this.originalCommand = originalCommand;
}
@Override
public Subscriber<? super R> call(final Subscriber<? super R> child) {
final CompositeSubscription s = new CompositeSubscription();
// if the child unsubscribes we unsubscribe our parent as well
child.add(s);
//超时的时候抛出new HystrixTimeoutException()
final HystrixContextRunnable timeoutRunnable = new HystrixContextRunnable(originalCommand.concurrencyStrategy, new Runnable() {
@Override
public void run() {
child.onError(new HystrixTimeoutException());
}
});
//设置定时调度
TimerListener listener = new TimerListener() {
//定时触发的方法
@Override
public void tick() {
//把状态从未执行设为timeout
if (originalCommand.isCommandTimedOut.compareAndSet(TimedOutStatus.NOT_EXECUTED, TimedOutStatus.TIMED_OUT)) {
// report timeout failure
originalCommand.eventNotifier.markEvent(HystrixEventType.TIMEOUT, originalCommand.commandKey);
// shut down the original request
s.unsubscribe();
timeoutRunnable.run();
}
}
//获取定时的的时间
@Override
public int getIntervalTimeInMilliseconds() {
return originalCommand.properties.executionTimeoutInMilliseconds().get();
}
};
final Reference<TimerListener> tl = HystrixTimer.getInstance().addTimerListener(listener);
// set externally so execute/queue can see this
originalCommand.timeoutTimer.set(tl);
/**
* If this subscriber receives values it means the parent succeeded/completed
*/
Subscriber<R> parent = new Subscriber<R>() {
...
};
// if s is unsubscribed we want to unsubscribe the parent
s.add(parent);
return parent;
}
}
public Reference<TimerListener> addTimerListener(final TimerListener listener) {
startThreadIfNeeded();
// add the listener
Runnable r = new Runnable() {
@Override
public void run() {
try {
listener.tick();
} catch (Exception e) {
logger.error("Failed while ticking TimerListener", e);
}
}
};
//getIntervalTimeInMilliseconds获取定时时间
ScheduledFuture<?> f = executor.get().getThreadPool().scheduleAtFixedRate(r, listener.getIntervalTimeInMilliseconds(), listener.getIntervalTimeInMilliseconds(), TimeUnit.MILLISECONDS);
return new TimerReference(listener, f);
}
主要逻辑，定义了一个定时器TimerListener，里面定时的时间就是我们设置的@HystrixCommand的超时的时间。如果超时了执行：
- 把状态从NOT_EXECUTED设置为TIMED_OUT
- 发送TIMEOUT事件
- s.unsubscribe()取消事件订阅
- timeoutRunnable.run();抛出timeoutRunnable异常
归纳一下就是设置了一个定时器，定时时间是我们设置的超时时间，如果定时时间到了，我们就改变相应的状态，发送相应的内部事件，取消Obserable的订阅，抛出异常，而做到一个超时的隔离。
再看看executeCommandWithSpecifiedIsolation方法
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() {
...
metrics.markCommandStart(commandKey, threadPoolKey, ExecutionIsolationStrategy.THREAD);
if (isCommandTimedOut.get() == TimedOutStatus.TIMED_OUT) {
...
return Observable.error(new RuntimeException("timed out before executing run()"));
}
if (threadState.compareAndSet(ThreadState.NOT_USING_THREAD, ThreadState.STARTED)) {
....
try {
executionHook.onThreadStart(_cmd);
executionHook.onRunStart(_cmd);
executionHook.onExecutionStart(_cmd);
//最后执行这个
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(...).doOnUnsubscribe(...)
//这个方法是用于指定一个线程池去执行我们被观察者observable触发时的方法
.subscribeOn(threadPool.getScheduler(new Func0<Boolean>() {
@Override
public Boolean call() {
return properties.executionIsolationThreadInterruptOnTimeout().get() && _cmd.isCommandTimedOut.get() == TimedOutStatus.TIMED_OUT;
}
}));
} else {
...
}
}
五，指定线程池执行方法
在executeCommandWithSpecifiedIsolation这个方法里的subscribeOn调用用于指定一个线程池去执行我们被观察者observable触发时的方法
/* package */static class HystrixThreadPoolDefault implements HystrixThreadPool {
private static final Logger logger = LoggerFactory.getLogger(HystrixThreadPoolDefault.class);
private final HystrixThreadPoolProperties properties;
private final BlockingQueue<Runnable> queue;
private final ThreadPoolExecutor threadPool;
private final HystrixThreadPoolMetrics metrics;
private final int queueSize;
...
@Override
public Scheduler getScheduler(Func0<Boolean> shouldInterruptThread) {
touchConfig();
return new HystrixContextScheduler(HystrixPlugins.getInstance().getConcurrencyStrategy(), this, shouldInterruptThread);
}
//动态调整线程池的大小
// allow us to change things via fast-properties by setting it each time
private void touchConfig() {
final int dynamicCoreSize = properties.coreSize().get();
final int configuredMaximumSize = properties.maximumSize().get();
int dynamicMaximumSize = properties.actualMaximumSize();
final boolean allowSizesToDiverge = properties.getAllowMaximumSizeToDivergeFromCoreSize().get();
boolean maxTooLow = false;
if (allowSizesToDiverge && configuredMaximumSize < dynamicCoreSize) {
dynamicMaximumSize = dynamicCoreSize;
maxTooLow = true;
}
// In JDK 6, setCorePoolSize and setMaximumPoolSize will execute a lock operation. Avoid them if the pool size is not changed.
if (threadPool.getCorePoolSize() != dynamicCoreSize || (allowSizesToDiverge && threadPool.getMaximumPoolSize() != dynamicMaximumSize)) {
...
threadPool.setCorePoolSize(dynamicCoreSize);
threadPool.setMaximumPoolSize(dynamicMaximumSize);
}
threadPool.setKeepAliveTime(properties.keepAliveTimeMinutes().get(), TimeUnit.MINUTES);
}
}
public class HystrixContextScheduler extends Scheduler {
private final HystrixConcurrencyStrategy concurrencyStrategy;
private final Scheduler actualScheduler;
private final HystrixThreadPool threadPool;
。。。
public HystrixContextScheduler(HystrixConcurrencyStrategy concurrencyStrategy, HystrixThreadPool threadPool, Func0<Boolean> shouldInterruptThread) {
this.concurrencyStrategy = concurrencyStrategy;
this.threadPool = threadPool;
this.actualScheduler = new ThreadPoolScheduler(threadPool, shouldInterruptThread);
}
@Override
public Worker createWorker() {
// 构建一个默认的Worker,这里的actualScheduler就是ThreadPoolScheduler
//actualScheduler.createWorker()就是ThreadPoolWorker
return new HystrixContextSchedulerWorker(actualScheduler.createWorker());
}
//HystrixContextSchedulerWorker类
private class HystrixContextSchedulerWorker extends Worker {
private final Worker worker;
private HystrixContextSchedulerWorker(Worker actualWorker) {
this.worker = actualWorker;
}
...
@Override
public Subscription schedule(Action0 action) {
if (threadPool != null) {
if (!threadPool.isQueueSpaceAvailable()) {
throw new RejectedExecutionException("Rejected command because thread-pool queueSize is at rejection threshold.");
}
}
//这里的worker其实就是ThreadPoolWorker
return worker.schedule(new HystrixContexSchedulerAction(concurrencyStrategy, action));
}
}
//ThreadPoolScheduler类
private static class ThreadPoolScheduler extends Scheduler {
private final HystrixThreadPool threadPool;
private final Func0<Boolean> shouldInterruptThread;
public ThreadPoolScheduler(HystrixThreadPool threadPool, Func0<Boolean> shouldInterruptThread) {
this.threadPool = threadPool;
this.shouldInterruptThread = shouldInterruptThread;
}
@Override
public Worker createWorker() {
//默认的worker为：ThreadPoolWorker
return new ThreadPoolWorker(threadPool, shouldInterruptThread);
}
}
//ThreadPoolWorker类
private static class ThreadPoolWorker extends Worker {
private final HystrixThreadPool threadPool;
private final CompositeSubscription subscription = new CompositeSubscription();
private final Func0<Boolean> shouldInterruptThread;
public ThreadPoolWorker(HystrixThreadPool threadPool, Func0<Boolean> shouldInterruptThread) {
this.threadPool = threadPool;
this.shouldInterruptThread = shouldInterruptThread;
}
...
@Override
public Subscription schedule(final Action0 action) {
if (subscription.isUnsubscribed()) {
// don't schedule, we are unsubscribed
return Subscriptions.unsubscribed();
}
// This is internal RxJava API but it is too useful.
ScheduledAction sa = new ScheduledAction(action);
subscription.add(sa);
sa.addParent(subscription);
// 获取线程池
ThreadPoolExecutor executor = (ThreadPoolExecutor) threadPool.getExecutor();
// 将包装后的HystrixCommand submit到线程池，然后返回FutureTask
FutureTask<?> f = (FutureTask<?>) executor.submit(sa);
sa.add(new FutureCompleterWithConfigurableInterrupt(f, shouldInterruptThread, executor));
return sa;
}
...
}
}
几个内部类的作用：
- HystrixContextSchedulerWorker: 对外提供schedule()方法，这里会判断线程池队列是否已经满，如果满了这会抛出异常：Rejected command because thread-pool queueSize is at rejection threshold。 如果配置的队列大小为-1 则默认返回true
- ThreadPoolScheduler：执行createWorker()方法，默认使用ThreadPoolWorker()类
- ThreadPoolWorker： 执行command的核心逻辑
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));
}
@Override
final protected Observable<R> getExecutionObservable() {
return Observable.defer(new Func0<Observable<R>>() {
@Override
public Observable<R> call() {
try {
//可以看到run()方法了。 HystrixCommand.run()其实就是我们自己写的代码里的方法
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());
}
});
}
最后可以看到会调用Observable.just(run()) ，这个就是我们我们自己写的代码里的方法，到这里就是我们整体的执行过程了。
java
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