SpringBoot中的线程池,你真的会用么?

前言

前两天做项目的时候,想提高一下插入表的性能优化,因为是两张表,先插旧的表,紧接着插新的表,一万多条数据就有点慢了

后面就想到了线程池ThreadPoolExecutor,而用的是Spring Boot项目,可以用Spring提供的对ThreadPoolExecutor封装的线程池ThreadPoolTaskExecutor,直接使用注解启用

使用步骤

先创建一个线程池的配置,让Spring Boot加载,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

@Configuration
@EnableAsync
public class ExecutorConfig {
    private static final Logger logger = LoggerFactory.getLogger(ExecutorConfig.class);

    @Value("${async.executor.thread.core_pool_size}")
    private int corePoolSize;
    @Value("${async.executor.thread.max_pool_size}")
    private int maxPoolSize;
    @Value("${async.executor.thread.queue_capacity}")
    private int queueCapacity;
    @Value("${async.executor.thread.name.prefix}")
    private String namePrefix;

    @Bean(name = "asyncServiceExecutor")
    public Executor asyncServiceExecutor() {
        logger.info("start asyncServiceExecutor");
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        //配置核心线程数
        executor.setCorePoolSize(corePoolSize);
        //配置最大线程数
        executor.setMaxPoolSize(maxPoolSize);
        //配置队列大小
        executor.setQueueCapacity(queueCapacity);
        //配置线程池中的线程的名称前缀
        executor.setThreadNamePrefix(namePrefix);

        // 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;
    }
}

@Value是我配置在application.properties,可以参考配置,自由定义

# 异步线程配置
# 配置核心线程数
async.executor.thread.core_pool_size = 5
# 配置最大线程数
async.executor.thread.max_pool_size = 5
# 配置队列大小
async.executor.thread.queue_capacity = 99999
# 配置线程池中的线程的名称前缀
async.executor.thread.name.prefix = async-service-

创建一个Service接口,是异步线程的接口

public interface AsyncService {
    /**
     * 执行异步任务
     * 可以根据需求,自己加参数拟定,我这里就做个测试演示
     */
    void executeAsync();
}

实现类

@Service
public class AsyncServiceImpl implements AsyncService {
    private static final Logger logger = LoggerFactory.getLogger(AsyncServiceImpl.class);

    @Override
    @Async("asyncServiceExecutor")
    public void executeAsync() {
        logger.info("start executeAsync");

        System.out.println("异步线程要做的事情");
        System.out.println("可以在这里执行批量插入等耗时的事情");

        logger.info("end executeAsync");
    }
}

将Service层的服务异步化,在executeAsync()方法上增加注解@Async("asyncServiceExecutor"),asyncServiceExecutor方法是前面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

接下来就是在Controller里或者是哪里通过注解@Autowired注入这个Service

@Autowired
private AsyncService asyncService;

@GetMapping("/async")
public void async(){
    asyncService.executeAsync();
}

用postmain或者其他工具来多次测试请求一下

2018-07-16 22:15:47.655  INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:47.655  INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:15:47.770  INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:47.770  INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:15:47.816  INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:47.816  INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:15:48.833  INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:48.834  INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:15:48.986  INFO 10516 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:48.987  INFO 10516 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync

通过以上日志可以发现,[async-service-]是有多个线程的,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;

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

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
import org.springframework.util.concurrent.ListenableFuture;

import java.util.concurrent.Callable;
import java.util.concurrent.Future;
import java.util.concurrent.ThreadPoolExecutor;

/**
 * @Author: ChenBin
 * @Date: 2018/7/16/0016 22:19
 */
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()

@Bean(name = "asyncServiceExecutor")
    public Executor asyncServiceExecutor() {
        logger.info("start asyncServiceExecutor");
        //在这里修改
        ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor();
        //配置核心线程数
        executor.setCorePoolSize(corePoolSize);
        //配置最大线程数
        executor.setMaxPoolSize(maxPoolSize);
        //配置队列大小
        executor.setQueueCapacity(queueCapacity);
        //配置线程池中的线程的名称前缀
        executor.setThreadNamePrefix(namePrefix);

        // 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;
    }

再次启动该工程测试

2018-07-16 22:23:30.951  INFO 14088 --- [nio-8087-exec-2] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [0], completedTaskCount [0], activeCount [0], queueSize [0]
2018-07-16 22:23:30.952  INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:30.953  INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:23:31.351  INFO 14088 --- [nio-8087-exec-3] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [1], completedTaskCount [1], activeCount [0], queueSize [0]
2018-07-16 22:23:31.353  INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:31.353  INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:23:31.927  INFO 14088 --- [nio-8087-exec-5] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [2], completedTaskCount [2], activeCount [0], queueSize [0]
2018-07-16 22:23:31.929  INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:31.930  INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync
2018-07-16 22:23:32.496  INFO 14088 --- [nio-8087-exec-7] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [3], completedTaskCount [3], activeCount [0], queueSize [0]
2018-07-16 22:23:32.498  INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl   : start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:32.499  INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl   : end executeAsync

注意这一行日志:

2018-07-16 22:23:32.496  INFO 14088 --- [nio-8087-exec-7] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [3], completedTaskCount [3], activeCount [0], queueSize [0]

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3个任务,完成了3个,当前有0个线程在处理任务,还剩0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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