springboot中@Async默认线程池导致OOM问题
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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