# 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");
}
}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
@Autowiredprivate
AsyncService asyncService;
@GetMapping("/async")
public void async(){
asyncService.executeAsync();
}日志打印
2022-07-16 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
2022-07-16 22:15:47.655 INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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
2022-07-16 22:15:47.770 INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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
2022-07-16 22:15:47.816 INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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
2022-07-16 22:15:48.834 INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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
2022-07-16 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: 腾腾
* @Date: 2022/7/16/0016 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 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()
@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
2022-07-16 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]
2022-07-16 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
2022-07-16 22:23:30.953 INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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]
2022-07-16 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
2022-07-16 22:23:31.353 INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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]
2022-07-16 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
2022-07-16 22:23:31.930 INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 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]
2022-07-16 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
2022-07-16 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：
2022-07-16 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。
