危险的Hystrix线程池

  • 时间:
  • 浏览:0

本文介绍Hystrix应用应用程序池的工作原理和参数配置,指出发生的难题并提供规避方案,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>

应用应用程序池和Hystrix Command之间的关系

当hystrix command的隔离策略配置为应用应用程序,也好多好多 我execution.isolation.strategy设置为THREAD时,command中的代码会塞进 应用应用程序池里执行,跟发起command调用的应用应用程序隔抛下。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

好十几个 线上的服务,往往会有好多好多 hystrix command分别用来管理不同的内部管理依赖。 或者有十几个 hystrix应用应用程序池发生呢,哪此command跟应用应用程序池的对应关系又是要怎样的呢,是一对一吗?

答案是不一定,command跟应用应用程序池需用做到一对一,但通常都有,受到HystrixThreadPoolKey和HystrixCommandGroupKey这两项配置的影响。

优先采用HystrixThreadPoolKey来标识应用应用程序池,或者越来越 配置HystrixThreadPoolKey越来越 就使用HystrixCommandGroupKey来标识。command跟应用应用程序池的对应关系,看多HystrixCommandKey、HystrixThreadPoolKey、HystrixCommandGroupKey两种好十几个 参数的配置。

获取应用应用程序池标识的代码如下,需用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会保证同好十几个 应用应用程序池标识只会创建好十几个 应用应用程序池:

    /*
     * 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应用应用程序池参数一览

  • coreSize 核心应用应用程序数量
  • maximumSize 最大应用应用程序数量
  • allowMaximumSizeToDivergeFromCoreSize 允许maximumSize大于coreSize,越来越配了两种值coreSize才有意义
  • keepAliveTimeMinutes 超过两种时间多于coreSize数量的应用应用程序会被回收,越来越maximumsize大于coreSize,两种值才有意义
  • maxQueueSize 任务队列的最大大小,当应用应用程序池的应用应用程序应用应用程序都有工作,好多好多 给你创建新的应用应用程序的也不,新的任务会进到队列里等待时间
  • queueSizeRejectionThreshold 任务队列中存储的任务数量超过两种值,应用应用程序池拒绝新的任务。这跟maxQueueSize越来越 是一回事,好多好多 我受限于hystrix的实现辦法 maxQueueSize越来越动态配置,好多好多 有了两种配置。

根据给定的应用应用程序池参数猜测应用应用程序池表现

需用看多hystrix的应用应用程序池参数跟JDK应用应用程序池ThreadPoolExecutor参数很像但又不一样,即便是完整篇 地看多文档,仍然给你迷惑。不过无妨,先来猜猜几种配置下的表现。

coreSize = 2; maxQueueSize = 10

应用应用程序池中常驻好十几个 应用应用程序。新任务提交到应用应用程序池,有空闲应用应用程序则直接执行,或者入队等待时间时间。等待时间队列中的任务数=10时,拒绝接受新任务。

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

应用应用程序池中常驻好十几个 应用应用程序。新任务提交到应用应用程序池,有空闲应用应用程序则直接执行,越来越 空闲应用应用程序时,或者当前应用应用程序数小于5则创建好十几个 新的应用应用程序用来执行任务,或者拒绝任务。

coreSize = 2; maximumSize = 5; maxQueueSize = 10

两种配置下从官方文档中或者看越来越了来实际表现会是要怎样的。猜测有如下两种或者:

  • 或者一。应用应用程序池中常驻好十几个 应用应用程序。新任务提交到应用应用程序池,好十几个 应用应用程序含有空闲则直接执行,或者入队等待时间时间。当好十几个 应用应用程序都有工作且等待时间队列中的任务数=10时,开始英文英文为新任务创建应用应用程序,直到应用应用程序数量为5,此时开始英文英文拒绝新任务。越来越 话语,对资源敏感型的任务比较友好,这也是JDK应用应用程序池ThreadPoolExecutor的行为。

  • 或者二。应用应用程序池中常驻好十几个 应用应用程序。新任务提交到应用应用程序池,有空闲应用应用程序则直接执行,越来越 空闲应用应用程序时,或者当前应用应用程序数小于5则创建好十几个 新的应用应用程序用来执行任务。当应用应用程序数量达到好十几个 且都有工作时,任务入队等待时间时间。等待时间队列中的任务数=10时,拒绝接受新任务。越来越 话语,对延迟敏感型的任务比较友好。

两种情况都有或者,从文档中无法选取究竟要怎样。

并发情况下Hystrix应用应用程序池的真正表现

本节中,通过测试来看看应用应用程序池的行为究竟会要怎样。

还是两种配置:

coreSize = 2; maximumSize = 5; maxQueueSize = 10

亲戚亲戚让让让我们通过不断提交任务到hystrix应用应用程序池,或者在任务的执行代码中使用CountDownLatch占住应用应用程序来模拟测试,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(1000);

    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(1000);

      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个应用应用程序在工作
Started Jobs: 2
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 0

// 任务数 > coreSize。此时仍然越来越coreSize个应用应用程序,多于coreSize的任务进入等待时间时间队列,越来越

创建新的应用应用程序  
Started Jobs: 7
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 5

// 任务数 = coreSize + maxQueueSize。此时仍然越来越coreSize个应用应用程序,多于coreSize的任务进入等待时间时间队列,越来越

创建新的应用应用程序  
Started Jobs: 12
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

// 任务数 > coreSize + maxQueueSize。此时仍然越来越coreSize个应用应用程序,等待时间时间队列已满,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

完整篇 的测试代码,参见这里

需用看多Hystrix应用应用程序池的实际表现,跟也不的两种猜测都有同,跟JDK应用应用程序池的表现不同,跟另两种合理猜测好多好多 我通。当maxSize > coreSize && maxQueueSize != -1的也不,maxSize两种参数根本就不起作用,应用应用程序数量永远不需要超过coreSize,对于的任务入队等待时间时间,队列满了,就直接拒绝新任务。

不得不说,这是两种给你疑惑的,非常危险的,容易配置错误的应用应用程序池表现。

JDK应用应用程序池ThreadPoolExecutor

继续分析Hystrix应用应用程序池的原理也不,先来复习一下JDK中的应用应用程序池。

只说跟本文讨论的内容相关的参数:

  • corePoolSize核心应用应用程序数,maximumPoolSize最大应用应用程序数。两种好十几个 参数跟hystrix应用应用程序池的coreSize和maximumSize含义是一致的。
  • workQueue任务等待时间时间队列。跟hystrix不同,jdk应用应用程序池的等待时间时间队列都有指定大小,好多好多 我需用使用方提供好十几个 BlockingQueue。
  • handler当应用应用程序池无法接受任务时的处理器。hystrix是直接拒绝,jdk应用应用程序池需用定制。

需用看多,jdk的应用应用程序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应用应用程序池底下allowMaximumSizeToDivergeFromCoreSize、queueSizeRejectionThreshold两种奇奇怪怪给你疑惑的参数。

关于jdk应用应用程序池的参数配置,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应用应用程序池对应的参数配置下,jdk应用应用程序池的表现会要怎样呢?

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。应用应用程序池中常驻好十几个 应用应用程序。新任务提交到应用应用程序池,好十几个 应用应用程序含有空闲则直接执行,或者入队等待时间时间。当好十几个 应用应用程序都有工作且等待时间队列中的任务数=10时,开始英文英文为新任务创建应用应用程序,直到应用应用程序数量为5,此时开始英文英文拒绝新任务。

相关逻辑涉及的源码贴在下面。值得一提的是,jdk应用应用程序池未必根据等待时间时间任务的数量来判断等待时间时间队列不是已满,好多好多 我直接调用workQueue的offer辦法 ,或者workQueue接受了那就入队等待时间时间,或者执行拒绝策略。

    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);
    }

需用看多hystrix应用应用程序池的配置参数跟jdk应用应用程序池是非常像的,从名字到含义,都基本一致。

为哪此

事实上hystrix的应用应用程序池,好多好多 我在jdk应用应用程序池的基础上实现的。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应用应用程序池基于jdk应用应用程序池实现,为哪此在如下好十几个 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在队列满了也不会创建应用应用程序执行新任务直到应用应用程序数量达到maximumPoolSize,而hystrix在队列满了也不直接拒绝新任务,maximumSize这项配置成了摆设。

原应就在于hystrix判断队列不是满不是要拒绝新任务,越来越 通过jdk应用应用程序池在判断,好多好多 我被委托人判断的。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);
    }

需用看多hystrix在队列大小达到maxQueueSize时,根本不需要往底层的ThreadPoolExecutor提交任务。ThreadPoolExecutor也就越来越 或者判断workQueue需用offer,更越来越创建新的应用应用程序了。

要怎样会会办

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应用应用程序池不为过。

那要怎样会会办呢?

配置的也不规避难题

一同配置maximumSize > coreSize,maxQueueSize > 0,像下面越来越 ,是不行了。

coreSize = 2; maximumSize = 5; maxQueueSize = 10

妥协一下,或者对延迟比较看重,配置maximumSize > coreSize,maxQueueSize = -1。越来越 在任务多的也不,不需要有等待时间时间队列,直接创建新应用应用程序执行任务。

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

或者对资源比较看重, 不希望创建不多应用应用程序,配置maximumSize = coreSize,maxQueueSize > 0。越来越 在任务多的也不,会进等待时间时间队列,直到有应用应用程序空闲或者超时。

coreSize = 2; maximumSize = 2; maxQueueSize = 10

在hystrix上修复两种难题

技术上是可行的,有好多好多 方案需用做到。但Netflix或者宣告不再维护hystrix了,这条路也就不通了,除非维护被委托人的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