一、@Async注解
@Async的作用就是异步处理任务。
在方法上添加@Async,表示此方法是异步方法;在类上添加@Async,表示类中的所有方法都是异步方法;使用此注解的类,必须是Spring管理的类;需要在启动类或配置类中加入@EnableAsync注解,@Async才会生效;在使用@Async时,如果不指定线程池的名称,也就是不自定义线程池,@Async是有默认线程池的,使用的是Spring默认的线程池SimpleAsyncTaskExecutor。
默认线程池的默认配置如下:
默认核心线程数:8;最大线程数:Integet.MAX_VALUE;队列使用LinkedBlockingQueue;容量是:Integet.MAX_VALUE;空闲线程保留时间:60s;线程池拒绝策略:AbortPolicy;从最大线程数可以看出,在并发情况下,会无限制的创建线程,我勒个吗啊。
也可以通过yml重新配置:
spring: task: execution: pool: max-size: 10 core-size: 5 keep-alive: 3s queue-capacity: 1000 thread-name-prefix: my-executor也可以自定义线程池,下面通过简单的代码来实现以下@Async自定义线程池。
二、代码实例
Spring为任务调度与异步方法执行提供了注解@Async支持,通过在方法上标注@Async注解,可使得方法被异步调用。在需要异步执行的方法上加入@Async注解,并指定使用的线程池,当然可以不指定,直接写@Async。
1、导入POM
<dependency> <groupId>com.google.guava</groupId> <artifactId>guava</artifactId> <version>31.0.1-jre</version></dependency>2、配置类
package com.nezhac.config;import com.google.common.util.concurrent.ThreadFactoryBuilder;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;import org.springframework.scheduling.annotation.EnableAsync;import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;import java.util.concurrent.*;@EnableAsync// 支持异步操作@Configurationpublic class AsyncTaskConfig { /** * com.google.guava中的线程池 * @return */ @Bean("my-executor") public Executor firstExecutor() { ThreadFactory threadFactory = new ThreadFactoryBuilder().setNameFormat("my-executor").build(); // 获取CPU的处理器数量 int curSystemThreads = Runtime.getRuntime().availableProcessors() * 2; ThreadPoolExecutor threadPool = new ThreadPoolExecutor(curSystemThreads, 100, 200, TimeUnit.SECONDS, new LinkedBlockingQueue<>(), threadFactory); threadPool.allowsCoreThreadTimeOut(); return threadPool; } /** * Spring线程池 * @return */ @Bean("async-executor") public Executor asyncExecutor() { ThreadPoolTaskExecutor taskExecutor = new ThreadPoolTaskExecutor(); // 核心线程数 taskExecutor.setCorePoolSize(10); // 线程池维护线程的最大数量,只有在缓冲队列满了之后才会申请超过核心线程数的线程 taskExecutor.setMaxPoolSize(100); // 缓存队列 taskExecutor.setQueueCapacity(50); // 空闲时间,当超过了核心线程数之外的线程在空闲时间到达之后会被销毁 taskExecutor.setKeepAliveSeconds(200); // 异步方法内部线程名称 taskExecutor.setThreadNamePrefix("async-executor-"); /** * 当线程池的任务缓存队列已满并且线程池中的线程数目达到maximumPoolSize,如果还有任务到来就会采取任务拒绝策略 * 通常有以下四种策略: * ThreadPoolExecutor.AbortPolicy:丢弃任务并抛出RejectedExecutionException异常。 * ThreadPoolExecutor.DiscardPolicy:也是丢弃任务,但是不抛出异常。 * ThreadPoolExecutor.DiscardOldestPolicy:丢弃队列最前面的任务,然后重新尝试执行任务(重复此过程) * ThreadPoolExecutor.CallerRunsPolicy:重试添加当前的任务,自动重复调用 execute() 方法,直到成功 */ taskExecutor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy()); taskExecutor.initialize(); return taskExecutor; }}3、controller
package com.nezha.controller;import com.nezha.service.UserService;import org.slf4j.Logger;import org.slf4j.LoggerFactory;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.scheduling.annotation.Async;import org.springframework.web.bind.annotation.GetMapping;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;@RestController@RequestMapping("/test")public class UserController { private static final Logger logger = LoggerFactory.getLogger(UserController.class); @Autowired private UserService userService; @GetMapping("asyncTest") public void asyncTest() { logger.info("1"); userService.asyncTest(); asyncTest2(); logger.info("1"); } @Async("my-executor") public void asyncTest2() { logger.info("同文件内执行执行异步任务"); }}4、service
package com.nezha.service;public interface UserService { // 普通方法 void test(); // 异步方法 void asyncTest();}service实现类
package com.nezha.service;import org.slf4j.Logger;import org.slf4j.LoggerFactory;import org.springframework.scheduling.annotation.Async;import org.springframework.stereotype.Service;@Servicepublic class UserServiceImpl implements UserService { private static final Logger logger = LoggerFactory.getLogger(UserServiceImpl.class); @Override public void test() { logger.info("执行普通任务"); } @Async("my-executor") @Override public void asyncTest() { logger.info("执行异步任务"); }}三、发现同文件内执行异步任务,还是一个线程,没有实现@Async效果,why?
众里寻他千百度,查到了@Async失效的几个原因:
注解@Async的方法不是public方法;注解@Async的返回值只能为void或Future;注解@Async方法使用static修饰也会失效;没加@EnableAsync注解;调用方和@Async不能在一个类中;在Async方法上标注@Transactional是没用的,但在Async方法调用的方法上标注@Transcational是有效的;这里就不一一演示了,有兴趣的小伙伴可以研究一下。
四、配置中分别使用了ThreadPoolTaskExecutor和ThreadPoolExecutor,这两个有啥区别?
ThreadPoolTaskExecutor是spring core包中的,而ThreadPoolExecutor是JDK中的JUC。ThreadPoolTaskExecutor是对ThreadPoolExecutor进行了封装。
1、initialize()
查看一下ThreadPoolTaskExecutor 的 initialize()方法
public abstract class ExecutorConfigurationSupport extends CustomizableThreadFactory implements BeanNameAware, InitializingBean, DisposableBean { ... /** * Set up the ExecutorService. */ public void initialize() { if (logger.isInfoEnabled()) { logger.info("Initializing ExecutorService" + (this.beanName != null ? " '" + this.beanName + "'" : "")); } if (!this.threadNamePrefixSet && this.beanName != null) { setThreadNamePrefix(this.beanName + "-"); } this.executor = initializeExecutor(this.threadFactory, this.rejectedExecutionHandler); } /** * Create the target {@link java.util.concurrent.ExecutorService} instance. * Called by {@code afterPropertiesSet}. * @param threadFactory the ThreadFactory to use * @param rejectedExecutionHandler the RejectedExecutionHandler to use * @return a new ExecutorService instance * @see #afterPropertiesSet() */ protected abstract ExecutorService initializeExecutor( ThreadFactory threadFactory, RejectedExecutionHandler rejectedExecutionHandler); ...}2、initializeExecutor抽象方法
再查看一下initializeExecutor抽象方法的具体实现类,其中有一个就是ThreadPoolTaskExecutor类,查看它的initializeExecutor方法,使用的就是ThreadPoolExecutor。
public class ThreadPoolTaskExecutor extends ExecutorConfigurationSupport implements AsyncListenableTaskExecutor, SchedulingTaskExecutor { ... @Override protected ExecutorService initializeExecutor( ThreadFactory threadFactory, RejectedExecutionHandler rejectedExecutionHandler) { BlockingQueue<Runnable> queue = createQueue(this.queueCapacity); ThreadPoolExecutor executor; if (this.taskDecorator != null) { executor = new ThreadPoolExecutor( this.corePoolSize, this.maxPoolSize, this.keepAliveSeconds, TimeUnit.SECONDS, queue, threadFactory, rejectedExecutionHandler) { @Override public void execute(Runnable command) { Runnable decorated = taskDecorator.decorate(command); if (decorated != command) { decoratedTaskMap.put(decorated, command); } super.execute(decorated); } }; } else { executor = new ThreadPoolExecutor( this.corePoolSize, this.maxPoolSize, this.keepAliveSeconds, TimeUnit.SECONDS, queue, threadFactory, rejectedExecutionHandler); } if (this.allowCoreThreadTimeOut) { executor.allowCoreThreadTimeOut(true); } this.threadPoolExecutor = executor; return executor; } ...}因此可以了解到ThreadPoolTaskExecutor是对ThreadPoolExecutor进行了封装。
五、核心线程数
配置文件中的线程池核心线程数为何配置为
// 获取CPU的处理器数量int curSystemThreads = Runtime.getRuntime().availableProcessors() * 2;Runtime.getRuntime().availableProcessors()获取的是CPU核心线程数,也就是计算资源。
CPU密集型,线程池大小设置为N,也就是和cpu的线程数相同,可以尽可能地避免线程间上下文切换,但在实际开发中,一般会设置为N+1,为了防止意外情况出现线程阻塞,如果出现阻塞,多出来的线程会继续执行任务,保证CPU的利用效率。IO密集型,线程池大小设置为2N,这个数是根据业务压测出来的,如果不涉及业务就使用推荐。在实际中,需要对具体的线程池大小进行调整,可以通过压测及机器设备现状,进行调整大小。如果线程池太大,则会造成CPU不断的切换,对整个系统性能也不会有太大的提升,反而会导致系统缓慢。
六、线程池执行过程