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;

有道无术,术可成;有术无道,止于术

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SpringBoot 线程池,也太好用了叭!_thread