Springboot线程池服务实战分享

我们常用ThreadPoolExecutor提供的线程池服务,springboot框架提供了@Async注解,帮助我们更方便的将业务逻辑提交到线程池中异步执行,今天我们就来实战体验这个线程池服务;

实战环境

windowns10;

jdk1.8;

springboot 1.5.9.RELEASE;

开发工具:IntelliJ IDEA;

这里面有多个工程,本次用到的工程为threadpooldemoserver,如下图红框所示:

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;

创建springboot工程

用IntelliJ IDEA创建一个springboot的web工程threadpooldemoserver,pom.xml内容如下:

    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">

    4.0.0

    com.bolingcavalry

    threadpooldemoserver

    0.0.1-SNAPSHOT

    jar

    threadpooldemoserver

    Demo project for Spring Boot

   

        org.springframework.boot

        spring-boot-starter-parent

        1.5.9.RELEASE

       

   

   

        UTF-8

        UTF-8

        1.8

   

   

       

            org.springframework.boot

            spring-boot-starter-web

       

   

   

       

           

                org.springframework.boot

                spring-boot-maven-plugin

           

       

   

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");

    }

}

这个方法做的事情很简单:sleep了一秒钟;

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;

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(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;

    }

}

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

将Service层的服务异步化

打开AsyncServiceImpl.java,在executeAsync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

将这个springboot运行起来(pom.xml所在文件夹下执行mvn spring-boot:run);

在浏览器输入:http://localhost:8080;

在浏览器用F5按钮快速多刷新几次;

在springboot的控制台看见日志如下:

2018-01-21 22:43:18.630  INFO 14824 --- [nio-8080-exec-8] c.b.t.controller.Hello                  : start submit

2018-01-21 22:43:18.630  INFO 14824 --- [nio-8080-exec-8] c.b.t.controller.Hello                  : end submit

2018-01-21 22:43:18.929  INFO 14824 --- [async-service-1] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:18.930  INFO 14824 --- [async-service-1] c.b.t.service.impl.AsyncServiceImpl      : start executeAsync

2018-01-21 22:43:19.005  INFO 14824 --- [async-service-2] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:19.006  INFO 14824 --- [async-service-2] c.b.t.service.impl.AsyncServiceImpl      : start executeAsync

2018-01-21 22:43:19.175  INFO 14824 --- [async-service-3] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:19.175  INFO 14824 --- [async-service-3] c.b.t.service.impl.AsyncServiceImpl      : start executeAsync

2018-01-21 22:43:19.326  INFO 14824 --- [async-service-4] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:19.495  INFO 14824 --- [async-service-5] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:19.930  INFO 14824 --- [async-service-1] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:20.006  INFO 14824 --- [async-service-2] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

2018-01-21 22:43:20.191  INFO 14824 --- [async-service-3] c.b.t.service.impl.AsyncServiceImpl      : end executeAsync

如上日志所示,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”,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 Future submit(Callable 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 ListenableFuture submitListenable(Callable 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;

至此,springboot线程池服务的实战就完成了,希望能帮您在工程中快速实现异步服务。

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