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springboot中@Async默认线程池导致OOM问题

ignorewho 人气:1

前言:

1.最近项目上在测试人员压测过程中发现了OOM问题,项目使用springboot搭建项目工程,通过查看日志中包含信息:unable to create new native thread

内存溢出的三种类型:
1.第一种OutOfMemoryError: PermGen space,发生这种问题的原意是程序中使用了大量的jar或class
2.第二种OutOfMemoryError: Java heap space,发生这种问题的原因是java虚拟机创建的对象太多
3.第三种OutOfMemoryError:unable to create new native thread,创建线程数量太多,占用内存过大

初步分析:

1.初步怀疑是线程创建太多导致,使用jstack 线程号 > /tmp/oom.log将应用的线程信息打印出来。查看oom.log,发现大量线程处于Runnable状态,基本可以确认是线程创建太多了。

代码分析:

1.出问题的微服务是日志写库服务,对比日志,锁定在writeLog方法上,wirteLog方法使用spring-@Async注解,写库操作采用的是异步写入方式。
2.之前没有对@Async注解深入研究过,只是知道可以自定义内部线程池,经查看,日志写库服务并未自定义异步配置,使用的是spring-@Async默认异步配置
3.首先简单百度了下,网上提到@Async默认异步配置使用的是SimpleAsyncTaskExecutor,该线程池默认来一个任务创建一个线程,在压测情况下,会有大量写库请求进入日志写库服务,这时就会不断创建大量线程,极有可能压爆服务器内存。

借此机会也学习了下SimpleAsyncTaskExecutor源码,总结如下:

1.SimpleAsyncTaskExecutor提供了限流机制,通过concurrencyLimit属性来控制开关,当concurrencyLimit>=0时开启限流机制,默认关闭限流机制即concurrencyLimit=-1,当关闭情况下,会不断创建新的线程来处理任务,核心代码如下:

public void execute(Runnable task, long startTimeout) {
  Assert.notNull(task, "Runnable must not be null");
  Runnable taskToUse = (this.taskDecorator != null ? this.taskDecorator.decorate(task) : task);
  //判断是否开启限流机制
  if (isThrottleActive() && startTimeout > TIMEOUT_IMMEDIATE) {
   //执行前置操作,进行限流
   this.concurrencyThrottle.beforeAccess();
   //执行完线程任务,会执行后置操作concurrencyThrottle.afterAccess(),配合进行限流
   doExecute(new ConcurrencyThrottlingRunnable(taskToUse));
  }
  else {
   doExecute(taskToUse);
  }
}

2.SimpleAsyncTaskExecutor限流实现

首先任务进来,会循环判断当前执行线程数是否超过concurrencyLimit,如果超了,则当前线程调用wait方法,释放monitor对象锁,进入等待

protected void beforeAccess() {
	if (this.concurrencyLimit == NO_CONCURRENCY) {
		throw new IllegalStateException(
				"Currently no invocations allowed - concurrency limit set to NO_CONCURRENCY");
	}
	if (this.concurrencyLimit > 0) {
		boolean debug = logger.isDebugEnabled();
		synchronized (this.monitor) {
			boolean interrupted = false;
			while (this.concurrencyCount >= this.concurrencyLimit) {
				if (interrupted) {
					throw new IllegalStateException("Thread was interrupted while waiting for invocation access, " +
							"but concurrency limit still does not allow for entering");
				}
				if (debug) {
					logger.debug("Concurrency count " + this.concurrencyCount +
							" has reached limit " + this.concurrencyLimit + " - blocking");
				}
				try {
					this.monitor.wait();
				}
				catch (InterruptedException ex) {
					// Re-interrupt current thread, to allow other threads to react.
					Thread.currentThread().interrupt();
					interrupted = true;
				}
			}
			if (debug) {
				logger.debug("Entering throttle at concurrency count " + this.concurrencyCount);
			}
			this.concurrencyCount++;
		}
	}
}

2.SimpleAsyncTaskExecutor限流实现:首先任务进来,会循环判断当前执行线程数是否超过concurrencyLimit,如果超了,则当前线程调用wait方法,释放monitor对象锁,进入等待状态。

protected void beforeAccess() {
	if (this.concurrencyLimit == NO_CONCURRENCY) {
		throw new IllegalStateException(
				"Currently no invocations allowed - concurrency limit set to NO_CONCURRENCY");
	}
	if (this.concurrencyLimit > 0) {
		boolean debug = logger.isDebugEnabled();
		synchronized (this.monitor) {
			boolean interrupted = false;
			while (this.concurrencyCount >= this.concurrencyLimit) {
				if (interrupted) {
					throw new IllegalStateException("Thread was interrupted while waiting for invocation access, " +
							"but concurrency limit still does not allow for entering");
				}
				if (debug) {
					logger.debug("Concurrency count " + this.concurrencyCount +
							" has reached limit " + this.concurrencyLimit + " - blocking");
				}
				try {
					this.monitor.wait();
				}
				catch (InterruptedException ex) {
					// Re-interrupt current thread, to allow other threads to react.
					Thread.currentThread().interrupt();
					interrupted = true;
				}
			}
			if (debug) {
				logger.debug("Entering throttle at concurrency count " + this.concurrencyCount);
			}
			this.concurrencyCount++;
		}
	}
}

线程任务执行完毕后,当前执行线程数会减一,会调用monitor对象的notify方法,唤醒等待状态下的线程,等待状态下的线程会竞争monitor锁,竞争到,会继续执行线程任务。

protected void afterAccess() {
	if (this.concurrencyLimit >= 0) {
		synchronized (this.monitor) {
			this.concurrencyCount--;
			if (logger.isDebugEnabled()) {
				logger.debug("Returning from throttle at concurrency count " + this.concurrencyCount);
			}
			this.monitor.notify();
		}
	}
}

虽然看了源码了解了SimpleAsyncTaskExecutor有限流机制,实践出真知,我们还是测试下:
一、测试未开启限流机制下,我们启动20个线程去调用异步方法,查看Java VisualVM工具如下:


二、测试开启限流机制,开启限流机制的代码如下:

@Configuration
@EnableAsync
public class AsyncCommonConfig extends AsyncConfigurerSupport {
  @Override
  public Executor getAsyncExecutor() {
    SimpleAsyncTaskExecutor executor = new SimpleAsyncTaskExecutor();
    //设置允许同时执行的线程数为10
 executor.setConcurrencyLimit(10);
    return executor;
  }
}

同样,我们启动20个线程去调用异步方法,查看Java VisualVM工具如下:

通过上面验证可知:
1.开启限流情况下,能有效控制应用线程数
2.虽然可以有效控制线程数,但执行效率会降低,会出现主线程等待,线程竞争的情况。
3.限流机制适用于任务处理比较快的场景,对于应用处理时间比较慢的场景并不适用。==

最终解决办法:
1.自定义线程池,使用LinkedBlockingQueue阻塞队列来限定线程池的上限
2.定义拒绝策略,如果队列满了,则拒绝处理该任务,打印日志,代码如下:

public class AsyncConfig implements AsyncConfigurer{
  private Logger logger = LogManager.getLogger();

  @Value("${thread.pool.corePoolSize:10}")
  private int corePoolSize;

  @Value("${thread.pool.maxPoolSize:20}")
  private int maxPoolSize;

  @Value("${thread.pool.keepAliveSeconds:4}")
  private int keepAliveSeconds;

  @Value("${thread.pool.queueCapacity:512}")
  private int queueCapacity;

  @Override
  public Executor getAsyncExecutor() {
    ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
    executor.setCorePoolSize(corePoolSize);
    executor.setMaxPoolSize(maxPoolSize);
    executor.setKeepAliveSeconds(keepAliveSeconds);
    executor.setQueueCapacity(queueCapacity);
    executor.setRejectedExecutionHandler((Runnable r, ThreadPoolExecutor exe) -> {
        logger.warn("当前任务线程池队列已满.");
    });
    executor.initialize();
    return executor;
  }

  @Override
  public AsyncUncaughtExceptionHandler getAsyncUncaughtExceptionHandler() {
    return new AsyncUncaughtExceptionHandler() {
      @Override
      public void handleUncaughtException(Throwable ex , Method method , Object... params) {
        logger.error("线程池执行任务发生未知异常.", ex);
      }
    };
  }
}

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