危险的Hystrix线程池

  • 时间:
  • 浏览:2
  • 来源:极速快3_快3平台网址_极速快3平台网址

本文介绍Hystrix应用系统进程池的工作原理和参数配置,指出存在的现象并提供规避方案,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,也就说 execution.isolation.strategy设置为THREAD时,command中的代码会装入应用系统进程池里执行,跟发起command调用的应用系统进程隔失去。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

另另有另另一个线上的服务,往往会有就说 hystrix command分别用来管理不同的内部内部结构依赖。 就说 有2个hystrix应用系统进程池存在呢,哪此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跟应用系统进程池都需用做到一对一,但通常需用,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,原困这样配置HystrixThreadPoolKey这样就使用HystrixCommandGroupKey来标识。command跟应用系统进程池的对应关系,看多HystrixCommandKey、HystrixThreadPoolKey、HystrixCommandGroupKey这另另有另另一个参数的配置。

获取应用系统进程池标识的代码如下,都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会保证同另另有另另一个应用系统进程池标识只会创建另另有另另一个应用系统进程池:

    /*
     * 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,必须配了一种值coreSize才有意义
  • keepAliveTimeMinutes 超过一种时间多于coreSize数量的应用系统进程会被回收,必须maximumsize大于coreSize,一种值才有意义
  • 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需用工作,就说 能创建新的应用系统进程的日后,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一种值,应用系统进程池拒绝新的任务。这跟maxQueueSize那我是一回事,就说 受限于hystrix的实现法子maxQueueSize必须动态配置,就说 有了一种配置。

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

都需用看多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,仍然我想要迷惑。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另另有另另一个应用系统进程。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,就说 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

应用系统进程池中常驻另另有另另一个应用系统进程。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,这样空闲应用系统进程时,原困当前应用系统进程数小于5则创建另另有另另一个新的应用系统进程用来执行任务,就说 拒绝任务。

coreSize = 2; maximumSize = 5; maxQueueSize = 10

一种配置下从官方文档中原困看这样来实际表现会是如何的。猜测有如下一种原困:

  • 原困一。应用系统进程池中常驻另另有另另一个应用系统进程。新任务提交到应用系统进程池,另另有另另一个应用系统进程中有 空闲则直接执行,就说 入队等待时间时间。当另另有另另一个应用系统进程需用工作且等待时间队列中的任务数=10时,开始英语 英语 为新任务创建应用系统进程,直到应用系统进程数量为5,此时开始英语 英语 拒绝新任务。那我一段话,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。

  • 原困二。应用系统进程池中常驻另另有另另一个应用系统进程。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,这样空闲应用系统进程时,原困当前应用系统进程数小于5则创建另另有另另一个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另一个且需用工作时,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。那我一段话,对延迟敏感型的任务比较友好。

一种具体情况需用原困,从文档中无法选折 究竟如何。

并发具体情况下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。

还是一种配置:

coreSize = 2; maximumSize = 5; maxQueueSize = 10

大家通过不断提交任务到hystrix应用系统进程池,就说 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(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个应用系统进程在工作
Started Jobs: 2
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 0

// 任务数 > coreSize。此时仍然必须coreSize个应用系统进程,多于coreSize的任务进入等待时间时间队列,这样创建新的应用系统进程  
Started Jobs: 7
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 5

// 任务数 = coreSize + maxQueueSize。此时仍然必须coreSize个应用系统进程,多于coreSize的任务进入等待时间时间队列,这样创建新的应用系统进程  
Started Jobs: 12
ThreadPoolKey: TestThreadPoolCommand, PoolSize: 2, QueueSize: 10

// 任务数 > coreSize + maxQueueSize。此时仍然必须coreSize个应用系统进程,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

全版的测试代码,参见这里

都需用看多Hystrix应用系统进程池的实际表现,跟日后的一种猜测需用同,跟JDK应用系统进程池的表现不同,跟另一种合理猜测就说 通。当maxSize > coreSize && maxQueueSize != -1的日后,maxSize一种参数根本就不起作用,应用系统进程数量永远不想超过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,这是一种我想要疑惑的,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日后,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。一种另另有另另一个参数跟hystrix应用系统进程池的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应用系统进程池的等待时间时间队列需用指定大小,就说 需用使用方提供另另有另另一个BlockingQueue。
  • handler当应用系统进程池无法接受任务时的出理 器。hystrix是直接拒绝,jdk应用系统进程池都需用定制。

都需用看多,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,这样hystrx应用系统进程池里面allowMaximumSizeToDivergeFromCoreSize、queueSizeRejectionThreshold一种奇奇怪怪我想要疑惑的参数。

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;
    }

这样在跟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另另有另另一个应用系统进程。新任务提交到应用系统进程池,另另有另另一个应用系统进程中有 空闲则直接执行,就说 入队等待时间时间。当另另有另另一个应用系统进程需用工作且等待时间队列中的任务数=10时,开始英语 英语 为新任务创建应用系统进程,直到应用系统进程数量为5,此时开始英语 英语 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应用系统进程池并不根据等待时间时间任务的数量来判断等待时间时间队列是是是不是已满,就说 直接调用workQueue的offer法子,原困workQueue接受了那就入队等待时间时间,就说 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);
    }

都需用看多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。

为哪此

事实上hystrix的应用系统进程池,就说 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,为哪此在如下另另有另另一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在队列满了过前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在队列满了日后直接拒绝新任务,maximumSize这项配置成了摆设。

原困就在于hystrix判断队列是是是不是满是是是不是要拒绝新任务,这样通过jdk应用系统进程池在判断,就说 当时人判断的。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);
    }

都需用看多hystrix在队列大小达到maxQueueSize时,根本不想往底层的ThreadPoolExecutor提交任务。ThreadPoolExecutor也就这样原困判断workQueue都需用offer,更必须创建新的应用系统进程了。

缘何办

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。

那缘何办呢?

配置的日后规避现象

一块儿配置maximumSize > coreSize,maxQueueSize > 0,像下面那我,是不行了。

coreSize = 2; maximumSize = 5; maxQueueSize = 10

妥协一下,原困对延迟比较看重,配置maximumSize > coreSize,maxQueueSize = -1。那我在任务多的日后,不想有等待时间时间队列,直接创建新应用系统进程执行任务。

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

原困对资源比较看重, 不希望创建太多应用系统进程,配置maximumSize = coreSize,maxQueueSize > 0。那我在任务多的日后,会进等待时间时间队列,直到有应用系统进程空闲原困超时。

coreSize = 2; maximumSize = 2; maxQueueSize = 10

在hystrix上修复一种现象

技术上是可行的,有就说 方案都需用做到。但Netflix原困否认不再维护hystrix了,这条路也就不通了,除非维护当时人的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