危险的Hystrix线程池

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本文介绍Hystrix应用系统进程池的工作原理和参数配置,指出指在的疑问并提供规避方案,阅读本文需用对Hystrix有一定的了解。

文本讨论的内容,基于hystrix 1.5.18:

    <dependency>
      <groupId>com.netflix.hystrix</groupId>
      <artifactId>hystrix-core</artifactId>
      <version>1.5.18</version>
    </dependency>

应用系统进程池和Hystrix Command之间的关系

当hystrix command的隔离策略配置为应用系统进程,也只是我execution.isolation.strategy设置为THREAD时,command中的代码会放满应用系统进程池里执行,跟发起command调用的应用系统进程隔遗弃。摘要官方wiki如下:

execution.isolation.strategy

This property indicates which isolation strategy HystrixCommand.run() executes with, one of the following two choices:

THREAD — it executes on a separate thread and concurrent requests are limited by the number of threads in the thread-pool

SEMAPHORE — it executes on the calling thread and concurrent requests are limited by the semaphore count

二个 多多线上的服务,往往会有什么都hystrix command分别用来管理不同的内部管理依赖。 只是我有哪哪几个hystrix应用系统进程池指在呢,那先 command跟应用系统进程池的对应关系又是如何的呢,是一对一吗?

答案是不一定,command跟应用系统进程池能要能 做到一对一,但通常有的是,受到HystrixThreadPoolKey和HystrixCommandGroupKey这两项配置的影响。

优先采用HystrixThreadPoolKey来标识应用系统进程池,不可能 越来越 配置HystrixThreadPoolKey越来越 就使用HystrixCommandGroupKey来标识。command跟应用系统进程池的对应关系,看多HystrixCommandKey、HystrixThreadPoolKey、HystrixCommandGroupKey这二个多参数的配置。

获取应用系统进程池标识的代码如下,能要能 看多跟我的描述是一致的:

    /*
     * ThreadPoolKey
     *
     * This defines which thread-pool this command should run on.
     *
     * It uses the HystrixThreadPoolKey if provided, then defaults to use HystrixCommandGroup.
     *
     * It can then be overridden by a property if defined so it can be changed at runtime.
     */
    private static HystrixThreadPoolKey initThreadPoolKey(HystrixThreadPoolKey threadPoolKey, HystrixCommandGroupKey groupKey, String threadPoolKeyOverride) {
        if (threadPoolKeyOverride == null) {
            // we don't have a property overriding the value so use either HystrixThreadPoolKey or HystrixCommandGroup
            if (threadPoolKey == null) {
                /* use HystrixCommandGroup if HystrixThreadPoolKey is null */
                return HystrixThreadPoolKey.Factory.asKey(groupKey.name());
            } else {
                return threadPoolKey;
            }
        } else {
            // we have a property defining the thread-pool so use it instead
            return HystrixThreadPoolKey.Factory.asKey(threadPoolKeyOverride);
        }
    }

Hystrix会保证同二个 多多应用系统进程池标识只会创建二个 多多应用系统进程池:

    /*
     * Use the String from HystrixThreadPoolKey.name() instead of the HystrixThreadPoolKey instance as it's just an interface and we can't ensure the object
     * we receive implements hashcode/equals correctly and do not want the default hashcode/equals which would create a new threadpool for every object we get even if the name is the same
     */
    /* package */final static ConcurrentHashMap<String, HystrixThreadPool> threadPools = new ConcurrentHashMap<String, HystrixThreadPool>();

    /**
     * Get the {@link HystrixThreadPool} instance for a given {@link HystrixThreadPoolKey}.
     * <p>
     * This is thread-safe and ensures only 1 {@link HystrixThreadPool} per {@link HystrixThreadPoolKey}.
     *
     * @return {@link HystrixThreadPool} instance
     */
    /* package */static HystrixThreadPool getInstance(HystrixThreadPoolKey threadPoolKey, HystrixThreadPoolProperties.Setter propertiesBuilder) {
        // get the key to use instead of using the object itself so that if people forget to implement equals/hashcode things will still work
        String key = threadPoolKey.name();

        // this should find it for all but the first time
        HystrixThreadPool previouslyCached = threadPools.get(key);
        if (previouslyCached != null) {
            return previouslyCached;
        }

        // if we get here this is the first time so we need to initialize
        synchronized (HystrixThreadPool.class) {
            if (!threadPools.containsKey(key)) {
                threadPools.put(key, new HystrixThreadPoolDefault(threadPoolKey, propertiesBuilder));
            }
        }
        return threadPools.get(key);
    }

Hystrix应用系统进程池参数一览

  • coreSize 核心应用系统进程数量
  • maximumSize 最大应用系统进程数量
  • allowMaximumSizeToDivergeFromCoreSize 允许maximumSize大于coreSize,要能配了这些值coreSize才有意义
  • keepAliveTimeMinutes 超过这些时间多于coreSize数量的应用系统进程会被回收,要能maximumsize大于coreSize,这些值才有意义
  • maxQueueSize 任务队列的最大大小,当应用系统进程池的应用系统进程应用系统进程有的是工作,只是我能创建新的应用系统进程的然后,新的任务会进到队列里听候
  • queueSizeRejectionThreshold 任务队列中存储的任务数量超过这些值,应用系统进程池拒绝新的任务。这跟maxQueueSize越来越 是一回事,只是我受限于hystrix的实现土土办法 maxQueueSize要能动态配置,什么都了这些配置。

根据给定的应用系统进程池参数猜测应用系统进程池表现

能要能 看多hystrix的应用系统进程池参数跟JDK应用系统进程池ThreadPoolExecutor参数很像但又不一样,即便是全版地看多文档,仍然为什么会么会我要我迷惑。不过无妨,先来猜猜几种配置下的表现。

coreSize = 2; maxQueueSize = 10

应用系统进程池中常驻二个 多多应用系统进程。新任务提交到应用系统进程池,有空闲应用系统进程则直接执行,只是我入队听候。听候队列中的任务数=10时,拒绝接受新任务。

coreSize = 2; maximumSize = 5; maxQueueSize = -1

应用系统进程池中常驻二个 多多应用系统进程。新任务提交到应用系统进程池,有空闲应用系统进程则直接执行,越来越 空闲应用系统进程时,不可能 当前应用系统进程数小于5则创建二个 多多新的应用系统进程用来执行任务,只是我拒绝任务。

coreSize = 2; maximumSize = 5; maxQueueSize = 10

这些配置下从官方文档中不可能 看不在 来实际表现会是如何的。猜测有如下一种不可能 :

  • 不可能 一。应用系统进程池中常驻二个 多多应用系统进程。新任务提交到应用系统进程池,二个 多多应用系统进程中含空闲则直接执行,只是我入队听候。当二个 多多应用系统进程有的是工作且听候队列中的任务数=10时,开使了了为新任务创建应用系统进程,直到应用系统进程数量为5,此时开使了了拒绝新任务。越来越 句子,对资源敏感型的任务比较友好,这也是JDK应用系统进程池ThreadPoolExecutor的行为。

  • 不可能 二。应用系统进程池中常驻二个 多多应用系统进程。新任务提交到应用系统进程池,有空闲应用系统进程则直接执行,越来越 空闲应用系统进程时,不可能 当前应用系统进程数小于5则创建二个 多多新的应用系统进程用来执行任务。当应用系统进程数量达到二个且有的是工作时,任务入队听候。听候队列中的任务数=10时,拒绝接受新任务。越来越 句子,对延迟敏感型的任务比较友好。

一种情形有的是不可能 ,从文档中无法选者究竟如何。

并发情形下Hystrix应用系统进程池的真正表现

本节中,通过测试来看看应用系统进程池的行为究竟会如何。

还是这些配置:

coreSize = 2; maximumSize = 5; maxQueueSize = 10

这些人通过不断提交任务到hystrix应用系统进程池,只是我在任务的执行代码中使用CountDownLatch占住应用系统进程来模拟测试,代码如下:

public class HystrixThreadPoolTest {

  public static void main(String[] args) throws InterruptedException {
    final int coreSize = 2, maximumSize = 5, maxQueueSize = 10;
    final String commandName = "TestThreadPoolCommand";

    final HystrixCommand.Setter commandConfig = HystrixCommand.Setter
        .withGroupKey(HystrixCommandGroupKey.Factory.asKey(commandName))
        .andCommandKey(HystrixCommandKey.Factory.asKey(commandName))
        .andCommandPropertiesDefaults(
            HystrixCommandProperties.Setter()
                .withExecutionTimeoutEnabled(false))
        .andThreadPoolPropertiesDefaults(
            HystrixThreadPoolProperties.Setter()
                .withCoreSize(coreSize)
                .withMaximumSize(maximumSize)
                .withAllowMaximumSizeToDivergeFromCoreSize(true)
                .withMaxQueueSize(maxQueueSize)
                .withQueueSizeRejectionThreshold(maxQueueSize));

    // Run command once, so we can get metrics.
    HystrixCommand<Void> command = new HystrixCommand<Void>(commandConfig) {
      @Override protected Void run() throws Exception {
        return null;
      }
    };
    command.execute();
    Thread.sleep(100);

    final CountDownLatch stopLatch = new CountDownLatch(1);
    List<Thread> threads = new ArrayList<Thread>();

    for (int i = 0; i < coreSize + maximumSize + maxQueueSize; i++) {
      final int fi = i + 1;

      Thread thread = new Thread(new Runnable() {
        public void run() {
          try {
            HystrixCommand<Void> command = new HystrixCommand<Void>(commandConfig) {
              @Override protected Void run() throws Exception {
                stopLatch.await();
                return null;
              }
            };
            command.execute();
          } catch (HystrixRuntimeException e) {
            System.out.println("Started Jobs: " + fi);
            System.out.println("Job:" + fi + " got rejected.");
            printThreadPoolStatus();
            System.out.println();
          }
        }
      });
      threads.add(thread);
      thread.start();
      Thread.sleep(100);

      if(fi == coreSize || fi == coreSize + maximumSize || fi == coreSize + maxQueueSize ) {
        System.out.println("Started Jobs: " + fi);
        printThreadPoolStatus();
        System.out.println();
      }
    }

    stopLatch.countDown();

    for (Thread thread : threads) {
      thread.join();
    }

  }

  static void printThreadPoolStatus() {
    for (HystrixThreadPoolMetrics threadPoolMetrics : HystrixThreadPoolMetrics.getInstances()) {
      String name = threadPoolMetrics.getThreadPoolKey().name();
      Number poolSize = threadPoolMetrics.getCurrentPoolSize();
      Number queueSize = threadPoolMetrics.getCurrentQueueSize();
      System.out.println("ThreadPoolKey: " + name + ", PoolSize: " + poolSize + ", QueueSize: " + queueSize);
    }

  }

}

执行代码得到如下输出:

// 任务数 = coreSize。此时coreSize个应用系统进程在工作
Started Jobs: 2
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 0

// 任务数 > coreSize。此时仍然要能coreSize个应用系统进程,多于coreSize的任务进入听候队列,越来越



创建新的应用系统进程  
Started Jobs: 7
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 5

// 任务数 = coreSize + maxQueueSize。此时仍然要能coreSize个应用系统进程,多于coreSize的任务进入听候队列,越来越



创建新的应用系统进程  
Started Jobs: 12
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

// 任务数 > coreSize + maxQueueSize。此时仍然要能coreSize个应用系统进程,听候队列已满,新增任务被拒绝 
Started Jobs: 13
Job:13 got rejected.
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

Started Jobs: 14
Job:14 got rejected.
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

Started Jobs: 15
Job:15 got rejected.
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

Started Jobs: 16
Job:16 got rejected.
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

Started Jobs: 17
Job:17 got rejected.
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

全版的测试代码,参见这里

能要能 看多Hystrix应用系统进程池的实际表现,跟然后的一种猜测有的是同,跟JDK应用系统进程池的表现不同,跟另一种合理猜测只是我通。当maxSize > coreSize && maxQueueSize != -1的然后,maxSize这些参数根本就不起作用,应用系统进程数量永远太久再超过coreSize,对于的任务入队听候,队列满了,就直接拒绝新任务。

不得不说,这是一种为什么会么会我要我疑惑的,非常危险的,容易配置错误的应用系统进程池表现。

JDK应用系统进程池ThreadPoolExecutor

继续分析Hystrix应用系统进程池的原理然后,先来复习一下JDK中的应用系统进程池。

只说跟本文讨论的内容相关的参数:

  • corePoolSize核心应用系统进程数,maximumPoolSize最大应用系统进程数。这些二个 多多参数跟hystrix应用系统进程池的coreSize和maximumSize含义是一致的。
  • workQueue任务听候队列。跟hystrix不同,jdk应用系统进程池的听候队列有的是指定大小,只是我需用使用方提供二个 多多BlockingQueue。
  • handler当应用系统进程池无法接受任务时的处置器。hystrix是直接拒绝,jdk应用系统进程池能要能 定制。

能要能 看多,jdk的应用系统进程池使用起来更加灵活。配置参数的含义也十分清晰,越来越 hystrx应用系统进程池中间allowMaximumSizeToDivergeFromCoreSize、queueSizeRejectionThreshold这些奇奇怪怪为什么会么会我要我疑惑的参数。

关于jdk应用系统进程池的参数配置,参加如下jdk源码:


    /**
     * Creates a new {@code ThreadPoolExecutor} with the given initial
     * parameters.
     *
     * @param corePoolSize the number of threads to keep in the pool, even
     *        if they are idle, unless {@code allowCoreThreadTimeOut} is set
     * @param maximumPoolSize the maximum number of threads to allow in the
     *        pool
     * @param keepAliveTime when the number of threads is greater than
     *        the core, this is the maximum time that excess idle threads
     *        will wait for new tasks before terminating.
     * @param unit the time unit for the {@code keepAliveTime} argument
     * @param workQueue the queue to use for holding tasks before they are
     *        executed.  This queue will hold only the {@code Runnable}
     *        tasks submitted by the {@code execute} method.
     * @param threadFactory the factory to use when the executor
     *        creates a new thread
     * @param handler the handler to use when execution is blocked
     *        because the thread bounds and queue capacities are reached
     * @throws IllegalArgumentException if one of the following holds:<br>
     *         {@code corePoolSize < 0}<br>
     *         {@code keepAliveTime < 0}<br>
     *         {@code maximumPoolSize <= 0}<br>
     *         {@code maximumPoolSize < corePoolSize}
     * @throws NullPointerException if {@code workQueue}
     *         or {@code threadFactory} or {@code handler} is null
     */
    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> workQueue,
                              ThreadFactory threadFactory,
                              RejectedExecutionHandler handler) {
        if (corePoolSize < 0 ||
            maximumPoolSize <= 0 ||
            maximumPoolSize < corePoolSize ||
            keepAliveTime < 0)
            throw new IllegalArgumentException();
        if (workQueue == null || threadFactory == null || handler == null)
            throw new NullPointerException();
        this.corePoolSize = corePoolSize;
        this.maximumPoolSize = maximumPoolSize;
        this.workQueue = workQueue;
        this.keepAliveTime = unit.toNanos(keepAliveTime);
        this.threadFactory = threadFactory;
        this.handler = handler;
    }

越来越 在跟hystrix应用系统进程池对应的参数配置下,jdk应用系统进程池的表现会如何呢?

corePoolSize = 2; maximumPoolSize = 5; workQueue = new ArrayBlockingQueue(10); handler = new ThreadPoolExecutor.DiscardPolicy()

这里不再测试了,直接给出答案。应用系统进程池中常驻二个 多多应用系统进程。新任务提交到应用系统进程池,二个 多多应用系统进程中含空闲则直接执行,只是我入队听候。当二个 多多应用系统进程有的是工作且听候队列中的任务数=10时,开使了了为新任务创建应用系统进程,直到应用系统进程数量为5,此时开使了了拒绝新任务。

相关逻辑涉及的源码贴在下面。值得一提的是,jdk应用系统进程池太久再根据听候任务的数量来判断听候队列不是已满,只是我直接调用workQueue的offer土土办法 ,不可能 workQueue接受了那就入队听候,只是我执行拒绝策略。

    public void execute(Runnable command) {
        if (command == null)
            throw new NullPointerException();
        /*
         * Proceed in 3 steps:
         *
         * 1. If fewer than corePoolSize threads are running, try to
         * start a new thread with the given command as its first
         * task.  The call to addWorker atomically checks runState and
         * workerCount, and so prevents false alarms that would add
         * threads when it shouldn't, by returning false.
         *
         * 2. If a task can be successfully queued, then we still need
         * to double-check whether we should have added a thread
         * (because existing ones died since last checking) or that
         * the pool shut down since entry into this method. So we
         * recheck state and if necessary roll back the enqueuing if
         * stopped, or start a new thread if there are none.
         *
         * 3. If we cannot queue task, then we try to add a new
         * thread.  If it fails, we know we are shut down or saturated
         * and so reject the task.
         */
        int c = ctl.get();
        if (workerCountOf(c) < corePoolSize) {
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
        if (isRunning(c) && workQueue.offer(command)) {
            int recheck = ctl.get();
            if (! isRunning(recheck) && remove(command))
                reject(command);
            else if (workerCountOf(recheck) == 0)
                addWorker(null, false);
        }
        else if (!addWorker(command, false))
            reject(command);
    }

能要能 看多hystrix应用系统进程池的配置参数跟jdk应用系统进程池是非常像的,从名字到含义,都基本一致。

为那先

事实上hystrix的应用系统进程池,只是我在jdk应用系统进程池的基础上实现的。相关代码如下:


    public ThreadPoolExecutor getThreadPool(final HystrixThreadPoolKey threadPoolKey, HystrixThreadPoolProperties threadPoolProperties) {
        final ThreadFactory threadFactory = getThreadFactory(threadPoolKey);

        final boolean allowMaximumSizeToDivergeFromCoreSize = threadPoolProperties.getAllowMaximumSizeToDivergeFromCoreSize().get();
        final int dynamicCoreSize = threadPoolProperties.coreSize().get();
        final int keepAliveTime = threadPoolProperties.keepAliveTimeMinutes().get();
        final int maxQueueSize = threadPoolProperties.maxQueueSize().get();
        final BlockingQueue<Runnable> workQueue = getBlockingQueue(maxQueueSize);

        if (allowMaximumSizeToDivergeFromCoreSize) {
            final int dynamicMaximumSize = threadPoolProperties.maximumSize().get();
            if (dynamicCoreSize > dynamicMaximumSize) {
                logger.error("Hystrix ThreadPool configuration at startup for : " + threadPoolKey.name() + " is trying to set coreSize = " +
                        dynamicCoreSize + " and maximumSize = " + dynamicMaximumSize + ".  Maximum size will be set to " +
                        dynamicCoreSize + ", the coreSize value, since it must be equal to or greater than the coreSize value");
                return new ThreadPoolExecutor(dynamicCoreSize, dynamicCoreSize, keepAliveTime, TimeUnit.MINUTES, workQueue, threadFactory);
            } else {
                return new ThreadPoolExecutor(dynamicCoreSize, dynamicMaximumSize, keepAliveTime, TimeUnit.MINUTES, workQueue, threadFactory);
            }
        } else {
            return new ThreadPoolExecutor(dynamicCoreSize, dynamicCoreSize, keepAliveTime, TimeUnit.MINUTES, workQueue, threadFactory);
        }
    }

    public BlockingQueue<Runnable> getBlockingQueue(int maxQueueSize) {
        /*
         * We are using SynchronousQueue if maxQueueSize <= 0 (meaning a queue is not wanted).
         * <p>
         * SynchronousQueue will do a handoff from calling thread to worker thread and not allow queuing which is what we want.
         * <p>
         * Queuing results in added latency and would only occur when the thread-pool is full at which point there are latency issues
         * and rejecting is the preferred solution.
         */
        if (maxQueueSize <= 0) {
            return new SynchronousQueue<Runnable>();
        } else {
            return new LinkedBlockingQueue<Runnable>(maxQueueSize);
        }
    }

既然hystrix应用系统进程池基于jdk应用系统进程池实现,为那先 在如下二个 多多基本一致的配置上,行为却不一样呢?

//hystrix
coreSize = 2; maximumSize = 5; maxQueueSize = 10

//jdk
corePoolSize = 2; maximumPoolSize = 5; workQueue = new ArrayBlockingQueue(10); handler = new ThreadPoolExecutor.DiscardPolicy()

jdk在队列满了然后会创建应用系统进程执行新任务直到应用系统进程数量达到maximumPoolSize,而hystrix在队列满了然后直接拒绝新任务,maximumSize这项配置成了摆设。

愿因就在于hystrix判断队列不是满不是要拒绝新任务,越来越 通过jdk应用系统进程池在判断,只是我此人 判断的。参见如下hystrix源码:

    public boolean isQueueSpaceAvailable() {
        if (queueSize <= 0) {
            // we don't have a queue so we won't look for space but instead
            // let the thread-pool reject or not
            return true;
        } else {
            return threadPool.getQueue().size() < properties.queueSizeRejectionThreshold().get();
        }
    }

    public Subscription schedule(Action0 action, long delayTime, TimeUnit unit) {
        if (threadPool != null) {
            if (!threadPool.isQueueSpaceAvailable()) {
                throw new RejectedExecutionException("Rejected command because thread-pool queueSize is at rejection threshold.");
            }
        }
        return worker.schedule(new HystrixContexSchedulerAction(concurrencyStrategy, action), delayTime, unit);
    }

能要能 看多hystrix在队列大小达到maxQueueSize时,根本太久再往底层的ThreadPoolExecutor提交任务。ThreadPoolExecutor也就越来越 不可能 判断workQueue能要能 offer,更要能创建新的应用系统进程了。

为什么会么会办

对用惯了jdk的ThreadPoolExecutor的人来说,再用hystrix的确容易出错,笔者就曾在多个重要线上服务的代码里看多过错误的配置,称一声危险的hystrix应用系统进程池不为过。

那为什么会么会办呢?

配置的然后规避疑问

一起去配置maximumSize > coreSize,maxQueueSize > 0,像下面越来越 ,是不行了。

coreSize = 2; maximumSize = 5; maxQueueSize = 10

妥协一下,不可能 对延迟比较看重,配置maximumSize > coreSize,maxQueueSize = -1。越来越 在任务多的然后,太久再有听候队列,直接创建新应用系统进程执行任务。

coreSize = 2; maximumSize = 5; maxQueueSize = -1

不可能 对资源比较看重, 不希望创建太久应用系统进程,配置maximumSize = coreSize,maxQueueSize > 0。越来越 在任务多的然后,会进听候队列,直到有应用系统进程空闲不可能 超时。

coreSize = 2; maximumSize = 2; maxQueueSize = 10

在hystrix上修复这些疑问

技术上是可行的,有什么都方案能要能 做到。但Netflix不可能 组阁 不再维护hystrix了,这条路也就不通了,除非维护此人 的hystrix分支版本。

Reference

https://github.com/Netflix/Hystrix/wiki/Configuration

https://github.com/Netflix/Hystrix/issues/1589

https://github.com/Netflix/Hystrix/pull/1670