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Spring Boot 线程池的使用和扩展 - 转载

作者:互联网

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:

 

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;

 

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");
    }
}

 

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;

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");
    }

 

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;

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.java的asyncServiceExecutor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;

 

 

 

 

 

 

 

 

标签:service,executeAsync,Spring,Boot,submit,线程,executor,public
来源: https://www.cnblogs.com/Latiny/p/11004380.html