最近我们组杨青同学遇到一个使用线程池不当的问题:异步处理的线程池线程将主线程hang住了,分析代码发现是线程池的拒绝策略设置得不合理,设置为CallerRunsPolicy。当异步线程的执行效率降低时,阻塞队列满了,触发了拒绝策略,进而导致主线程hang死。
从这个问题中,我们学到了两点:
- 线程池的使用,需要充分分析业务场景后作出选择,必要的情况下需要自定义线程池;
- 线程池的运行状况,也需要监控
关于线程池的监控,我参考了《Java编程的艺术》中提供的思路实现的,分享下我的代码片段,如下:
public class AsyncThreadExecutor implements AutoCloseable {private static final int DEFAULT_QUEUE_SIZE = 1000;private static final int DEFAULT_POOL_SIZE = 10;@Setterprivate int queueSize = DEFAULT_QUEUE_SIZE;@Setterprivate int poolSize = DEFAULT_POOL_SIZE;/*** 用于周期性监控线程池的运行状态*/private final ScheduledExecutorService scheduledExecutorService =Executors.newSingleThreadScheduledExecutor(new BasicThreadFactory.Builder().namingPattern("async thread executor monitor").build());/*** 自定义异步线程池* (1)任务队列使用有界队列* (2)自定义拒绝策略*/private final ThreadPoolExecutor threadPoolExecutor =new ThreadPoolExecutor(poolSize, poolSize, 0, TimeUnit.MILLISECONDS, new ArrayBlockingQueue(queueSize),new BasicThreadFactory.Builder().namingPattern("async-thread-%d").build(),(r, executor) -> log.error("the async executor pool is full!!"));private final ExecutorService executorService = threadPoolExecutor;@PostConstructpublic void init() {scheduledExecutorService.scheduleAtFixedRate(() -> {/*** 线程池需要执行的任务数*/long taskCount = threadPoolExecutor.getTaskCount();/*** 线程池在运行过程中已完成的任务数*/long completedTaskCount = threadPoolExecutor.getCompletedTaskCount();/*** 曾经创建过的最大线程数*/long largestPoolSize = threadPoolExecutor.getLargestPoolSize();/*** 线程池里的线程数量*/long poolSize = threadPoolExecutor.getPoolSize();/*** 线程池里活跃的线程数量*/long activeCount = threadPoolExecutor.getActiveCount();log.info("async-executor monitor. taskCount:{}, completedTaskCount:{}, largestPoolSize:{}, poolSize:{}, activeCount:{}",taskCount, completedTaskCount, largestPoolSize, poolSize, activeCount);}, 0, 10, TimeUnit.MINUTES);}public void execute(Runnable task) {executorService.execute(task);}@Overridepublic void close() throws Exception {executorService.shutdown();}}
这里的主要思路是:(1)使用有界队列的固定数量线程池;(2)拒绝策略是将任务丢弃,但是需要记录错误日志;(3)使用一个调度线程池对业务线程池进行监控。
在查看监控日志的时候,看到下图所示的监控日志:

这里我对largestPooSize的含义比较困惑,按字面理解是“最大的线程池数量”,但是按照线程池的定义,maximumPoolSize和coreSize相同的时候(在这里,都是10),一个线程池里的最大线程数是10,那么为什么largestPooSize可以是39呢?我去翻这块的源码:
/*** Returns the largest number of threads that have ever* simultaneously been in the pool.** @return the number of threads*/public int getLargestPoolSize() {final ReentrantLock mainLock = this.mainLock;mainLock.lock();try {return largestPoolSize;} finally {mainLock.unlock();}}
注释的翻译是:返回在这个线程池里曾经同时存在过的线程数。再看这个变量largestPoolSize在ThreadExecutor中的赋值的地方,代码如下:
private boolean addWorker(Runnable firstTask, boolean core) {retry:for (;;) {int c = ctl.get();int rs = runStateOf(c);// Check if queue empty only if necessary.if (rs >= SHUTDOWN &&! (rs == SHUTDOWN &&firstTask == null &&! workQueue.isEmpty()))return false;for (;;) {int wc = workerCountOf(c);if (wc >= CAPACITY ||wc >= (core ? corePoolSize : maximumPoolSize))return false;if (compareAndIncrementWorkerCount(c))break retry;c = ctl.get(); // Re-read ctlif (runStateOf(c) != rs)continue retry;// else CAS failed due to workerCount change; retry inner loop}}boolean workerStarted = false;boolean workerAdded = false;Worker w = null;try {w = new Worker(firstTask);final Thread t = w.thread;if (t != null) {final ReentrantLock mainLock = this.mainLock;mainLock.lock();try {// Recheck while holding lock.// Back out on ThreadFactory failure or if// shut down before lock acquired.int rs = runStateOf(ctl.get());if (rs < SHUTDOWN ||(rs == SHUTDOWN && firstTask == null)) {if (t.isAlive()) // precheck that t is startablethrow new IllegalThreadStateException();workers.add(w);int s = workers.size();if (s > largestPoolSize)largestPoolSize = s;//这里这里!workerAdded = true;}} finally {mainLock.unlock();}if (workerAdded) {t.start();workerStarted = true;}}} finally {if (! workerStarted)addWorkerFailed(w);}return workerStarted;}
发现两点:
- largestPoolSize是worker集合的历史最大值,只增不减。largestPoolSize的大小是线程池曾创建的线程个数,跟线程池的容量无关;
- largestPoolSize<=maximumPoolSize。
PS:杨青同学是这篇文章的灵感来源,他做了很多压测。给了我很多思路,并跟我一起分析了一些代码。
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