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  • Spring Boot 线程池的使用和扩展

    转载:http://blog.csdn.net/boling_cavalry/article/details/79120268

    1、实战环境

    windowns10;

    jdk1.8;

    springboot 1.5.9.RELEASE;

    开发工具:IntelliJ IDEA;

     

    2、实战步骤梳理

    本次实战的步骤如下:

    • 创建springboot工程;
    • 创建Service层的接口和实现;
    • 创建controller,开发一个http服务接口,里面会调用service层的服务;
    • 创建线程池的配置;
    • 将Service层的服务异步化,这样每次调用都会都被提交到线程池异步执行;
    • 扩展ThreadPoolTaskExecutor,在提交任务到线程池的时候可以观察到当前线程池的情况;

     

    3 springboot的线程池配置

    创建一个配置类ExecutorConfig,用来定义如何创建一个ThreadPoolTaskExecutor,要使用@Configuration和@EnableAsync这两个注解,表示这是个配置类,并且是线程池的配置类,如下所示:

     

    @Configuration
    @EnableAsync
    public class ExecutorConfig {
    
        private static final Logger logger = LoggerFactory.getLogger(ExecutorConfig.class);
    
        @Bean
        public Executor asyncServiceExecutor() {
            logger.info("start asyncServiceExecutor");
            ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
            //配置核心线程数
            executor.setCorePoolSize(5);
            //配置最大线程数
            executor.setMaxPoolSize(5);
            //配置队列大小
            executor.setQueueCapacity(9999);
            //配置线程池中的线程的名称前缀
            executor.setThreadNamePrefix("async-service-");
    
            // rejection-policy:当pool已经达到max size的时候,如何处理新任务
            // CALLER_RUNS:不在新线程中执行任务,而是有调用者所在的线程来执行
            executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
            //执行初始化
            executor.initialize();
            return executor;
        }
    }

      注意,上面的方法名称为asyncServiceExecutor,稍后马上用到;

    4 创建Service层的接口和实现

    创建一个service层的接口AsyncService,如下:

    public interface AsyncService {
    
        /**
         * 执行异步任务
         */
        void executeAsync();
    }

      

    对应的AsyncServiceImpl,实现如下:

    @Service
    public class AsyncServiceImpl implements AsyncService {
    
        private static final Logger logger = LoggerFactory.getLogger(AsyncServiceImpl.class);
    
        @Override
        public void executeAsync() {
            logger.info("start executeAsync");
            try{
                Thread.sleep(1000);
            }catch(Exception e){
                e.printStackTrace();
            }
            logger.info("end executeAsync");
        }
    }

    5 创建controller

    创建一个controller为Hello,里面定义一个http接口,做的事情是调用Service层的服务,如下:

    @RestController
    public class Hello {
    
        private static final Logger logger = LoggerFactory.getLogger(Hello.class);
    
        @Autowired
        private AsyncService asyncService;
    
        @RequestMapping("/")
        public String submit(){
            logger.info("start submit");
    
            //调用service层的任务
            asyncService.executeAsync();
    
            logger.info("end submit");
    
            return "success";
        }
    }

    至此,我们已经做好了一个http请求的服务,里面做的事情其实是同步的,接下来我们就开始配置springboot的线程池服务,将service层做的事情都提交到线程池中去处理;

     

    6 将Service层的服务异步化

    打开AsyncServiceImpl,在对应的方法上增加注解@Async(“asyncServiceExecutor”),asyncServiceExecutor是前面ExecutorConfig.java中的方法名,表明executeAsync方法进入的线程池是asyncServiceExecutor方法创建的,如下:

        @Override
        @Async("asyncServiceExecutor")
        public void executeAsync() {
            logger.info("start executeAsync");
            try{
                Thread.sleep(1000);
            }catch(Exception e){
                e.printStackTrace();
            }
            logger.info("end executeAsync");
        }

    6 验证效果

    1. 将这个springboot运行起来(pom.xml所在文件夹下执行mvn spring-boot:run);
    2. 在浏览器输入:http://localhost:8080
    3. 在浏览器用F5按钮快速多刷新几次;
    4. 在springboot的控制台看见日志如下:

     

    在日志中我们可以看到controller的执行线程是"nio-8080-exec-8",这是tomcat的执行线程,而service层的日志显示线程名为“async-service-1,2,3。。。”,显然已经在我们配置的线程池中执行了,并且每次请求中,controller的起始和结束日志都是连续打印的,表明每次请求都快速响应了,而耗时的操作都留给线程池中的线程去异步执行;

    7 扩展ThreadPoolTaskExecutor

    虽然我们已经用上了线程池,但是还不清楚线程池当时的情况,有多少线程在执行,多少在队列中等待呢?这里我创建了一个ThreadPoolTaskExecutor的子类,在每次提交线程的时候都会将当前线程池的运行状况打印出来,代码如下:

     

    public class VisiableThreadPoolTaskExecutor extends ThreadPoolTaskExecutor {
        private static final Logger logger = LoggerFactory.getLogger(VisiableThreadPoolTaskExecutor.class);
    
        private void showThreadPoolInfo(String prefix){
            ThreadPoolExecutor threadPoolExecutor = getThreadPoolExecutor();
    
            if(null==threadPoolExecutor){
                return;
            }
    
            logger.info("{}, {},taskCount [{}], completedTaskCount [{}], activeCount [{}], queueSize [{}]",
                    this.getThreadNamePrefix(),
                    prefix,
                    threadPoolExecutor.getTaskCount(),
                    threadPoolExecutor.getCompletedTaskCount(),
                    threadPoolExecutor.getActiveCount(),
                    threadPoolExecutor.getQueue().size());
        }
    
        @Override
        public void execute(Runnable task) {
            showThreadPoolInfo("1. do execute");
            super.execute(task);
        }
    
        @Override
        public void execute(Runnable task, long startTimeout) {
            showThreadPoolInfo("2. do execute");
            super.execute(task, startTimeout);
        }
    
        @Override
        public Future<?> submit(Runnable task) {
            showThreadPoolInfo("1. do submit");
            return super.submit(task);
        }
    
        @Override
        public <T> Future<T> submit(Callable<T> task) {
            showThreadPoolInfo("2. do submit");
            return super.submit(task);
        }
    
        @Override
        public ListenableFuture<?> submitListenable(Runnable task) {
            showThreadPoolInfo("1. do submitListenable");
            return super.submitListenable(task);
        }
    
        @Override
        public <T> ListenableFuture<T> submitListenable(Callable<T> task) {
            showThreadPoolInfo("2. do submitListenable");
            return super.submitListenable(task);
        }
    }

    如上所示,showThreadPoolInfo方法中将任务总数、已完成数、活跃线程数,队列大小都打印出来了,然后Override了父类的execute、submit等方法,在里面调用showThreadPoolInfo方法,这样每次有任务被提交到线程池的时候,都会将当前线程池的基本情况打印到日志中;

    修改ExecutorConfig.javaasyncServiceExecutor方法,将ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor()改为ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor(),如下所示:

    @Bean
        public Executor asyncServiceExecutor() {
            logger.info("start asyncServiceExecutor");
            //使用VisiableThreadPoolTaskExecutor
            ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor();
            //配置核心线程数
            executor.setCorePoolSize(5);
            //配置最大线程数
            executor.setMaxPoolSize(5);
            //配置队列大小
            executor.setQueueCapacity(99999);
            //配置线程池中的线程的名称前缀
            executor.setThreadNamePrefix("async-service-");
    
            // rejection-policy:当pool已经达到max size的时候,如何处理新任务
            // CALLER_RUNS:不在新线程中执行任务,而是有调用者所在的线程来执行
            executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
            //执行初始化
            executor.initialize();
            return executor;
        }

    再次启动该工程,再浏览器反复刷新http://localhost:8080,看到的日志如下:

    2018-01-21 23:04:56.113  INFO 15580 --- [nio-8080-exec-1] c.b.t.e.VisiableThreadPoolTaskExecutor   : async-service-, 2. do submit,taskCount [99], completedTaskCount [85], activeCount [5], queueSize [9]
    2018-01-21 23:04:56.113  INFO 15580 --- [nio-8080-exec-1] c.b.t.controller.Hello                   : end submit
    2018-01-21 23:04:56.225  INFO 15580 --- [async-service-1] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync
    2018-01-21 23:04:56.225  INFO 15580 --- [async-service-1] c.b.t.service.impl.AsyncServiceImpl      : start executeAsync
    2018-01-21 23:04:56.240  INFO 15580 --- [nio-8080-exec-2] c.b.t.controller.Hello                   : start submit
    2018-01-21 23:04:56.240  INFO 15580 --- [nio-8080-exec-2] c.b.t.e.VisiableThreadPoolTaskExecutor   : async-service-, 2. do submit,taskCount [100], completedTaskCount [86], activeCount [5], queueSize [9]
    2018-01-21 23:04:56.240  INFO 15580 --- [nio-8080-exec-2] c.b.t.controller.Hello                   : end submit
    2018-01-21 23:04:56.298  INFO 15580 --- [async-service-2] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync
    2018-01-21 23:04:56.298  INFO 15580 --- [async-service-2] c.b.t.service.impl.AsyncServiceImpl      : start executeAsync
    2018-01-21 23:04:56.372  INFO 15580 --- [nio-8080-exec-3] c.b.t.controller.Hello                   : start submit
    2018-01-21 23:04:56.373  INFO 15580 --- [nio-8080-exec-3] c.b.t.e.VisiableThreadPoolTaskExecutor   : async-service-, 2. do submit,taskCount [101], completedTaskCount [87], activeCount [5], queueSize [9]
    2018-01-21 23:04:56.373  INFO 15580 --- [nio-8080-exec-3] c.b.t.controller.Hello                   : end submit
    2018-01-21 23:04:56.444  INFO 15580 --- [async-service-3] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync
    2018-01-21 23:04:56.445  INFO 15580 --- [async-service-3] c.b.t.service.impl.AsyncServiceImpl      : start executeAsync

    注意这一行日志:2. do submit,taskCount [101], completedTaskCount [87], activeCount [5], queueSize [9]

    这说明提交任务到线程池的时候,调用的是submit(Callable task)这个方法,当前已经提交了101个任务,完成了87个,当前有5个线程在处理任务,还剩9个任务在队列中等待,线程池的基本情况一路了然;

     

     

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  • 原文地址:https://www.cnblogs.com/Latiny/p/11004380.html
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