ThreadPoolService.java
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package com.diligrp.cashier.shared.service;
import java.util.concurrent.*;
/**
* 请谨慎使用此线程池工具类，通常建议根据特定的使用场景设置线程池参数，不建议使用统一的线程池配置
* JDK的线程池类并不能很好区分"计算密集型"和"IO密集型"任务类型，应该根据不同的任务类型去配置不同的参数
*/
public final class ThreadPoolService {
private static final int CPU_CORE_NUM = Runtime.getRuntime().availableProcessors();
private static final int CPU_MAX_POOL_SIZE = 100;
// private static final int IO_MAX_POOL_SIZE = 1000;
// CPU运算密集型任务的线程池实例
private static volatile ExecutorService cpuThreadPoll;
// IO密集型任务的线程池实例
private static volatile ExecutorService ioThreadPoll;
private ThreadPoolService() {
}
/**
* 获取运算密集型任务的线程池实例
* 通常建议根据特定的使用场景设置线程池参数，不建议使用统一的线程池配置
*/
public static ExecutorService getCpuThreadPoll() {
if (cpuThreadPoll == null) {
synchronized (ThreadPoolService.class) {
if (cpuThreadPoll == null) {
cpuThreadPoll = new ThreadPoolExecutor(CPU_CORE_NUM + 1, CPU_MAX_POOL_SIZE, 20,
TimeUnit.SECONDS, new LinkedBlockingQueue<>(100), new LazyRejectedExecutionHandler());
}
}
}
return cpuThreadPoll;
}
/**
* 获取IO密集型任务的线程池实例
* 通常建议根据特定的使用场景设置线程池参数，不建议使用统一的线程池配置
*/
public static ExecutorService getIoThreadPoll() {
if (ioThreadPoll == null) {
synchronized (ThreadPoolService.class) {
if (ioThreadPoll == null) {
ioThreadPoll = Executors.newVirtualThreadPerTaskExecutor();
// ioThreadPoll = new ThreadPoolExecutor(CPU_CORE_NUM + 1, IO_MAX_POOL_SIZE, 20,
// TimeUnit.SECONDS, new LinkedBlockingQueue<>(1000), new LazyRejectedExecutionHandler());
}
}
}
return ioThreadPoll;
}
private static class LazyRejectedExecutionHandler implements RejectedExecutionHandler {
@Override
public void rejectedExecution(Runnable task, ThreadPoolExecutor executor) {
boolean success = false;
try {
success = executor.getQueue().offer(task, 15, TimeUnit.SECONDS);
} catch (InterruptedException ex) {
Thread.currentThread().interrupt();
}
if (!success) {
throw new RejectedExecutionException("task queue is full");
}
}
}
}