title: java线程池使用 author: 哪吒 date: '2023-06-15'
点击勘误issues，哪吒感谢大家的阅读
Java线程池使用指南
1. 线程池基础使用
1.1 创建线程池的方式
方式一：使用Executors工具类（不推荐）
// 1. 固定大小线程池
ExecutorService fixedPool = Executors.newFixedThreadPool(5);// 2. 缓存线程池
ExecutorService cachedPool = Executors.newCachedThreadPool();// 3. 单线程池
ExecutorService singlePool = Executors.newSingleThreadExecutor();// 4. 定时任务线程池
ScheduledExecutorService scheduledPool = Executors.newScheduledThreadPool(3);为什么不推荐使用Executors？
问题分析：
┌─────────────────────────────────────────────────────────┐
│ newFixedThreadPool & newSingleThreadExecutor │
│ ↓ │
│ 使用LinkedBlockingQueue（无界队列） │
│ ↓ │
│ 可能导致内存溢出（OOM） │
│ │
│ newCachedThreadPool │
│ ↓ │
│ 最大线程数为Integer.MAX_VALUE │
│ ↓ │
│ 可能创建大量线程导致系统崩溃 │
└─────────────────────────────────────────────────────────┘方式二：手动创建ThreadPoolExecutor（推荐）
public class ThreadPoolFactory {/*** 创建标准线程池*/public static ThreadPoolExecutor createStandardPool() {returnnew ThreadPoolExecutor(5, // 核心线程数10, // 最大线程数60L, // 空闲时间TimeUnit.SECONDS, // 时间单位new ArrayBlockingQueue<>(100), // 工作队列new ThreadFactory() { // 线程工厂privatefinal AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread t = new Thread(r, "CustomPool-" + threadNumber.getAndIncrement());t.setDaemon(false); // 设置为用户线程t.setPriority(Thread.NORM_PRIORITY);return t;}},new ThreadPoolExecutor.CallerRunsPolicy() // 拒绝策略);}
}2. 常用线程池类型及应用场景
2.1 CPU密集型任务线程池
public class CPUIntensiveThreadPool {/*** CPU密集型任务线程池配置* 核心线程数 = CPU核心数 + 1*/public static ThreadPoolExecutor createCPUIntensivePool() {int corePoolSize = Runtime.getRuntime().availableProcessors() + 1;returnnew ThreadPoolExecutor(corePoolSize,corePoolSize,0L,TimeUnit.MILLISECONDS,new LinkedBlockingQueue<>(50),new ThreadFactory() {privatefinal AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread t = new Thread(r, "CPU-Pool-" + threadNumber.getAndIncrement());t.setDaemon(false);return t;}},new ThreadPoolExecutor.AbortPolicy());}// 使用示例：计算密集型任务public static void main(String[] args) {ThreadPoolExecutor executor = createCPUIntensivePool();// 提交计算任务for (int i = 0; i < 10; i++) {finalint taskId = i;executor.submit(() -> {long result = fibonacci(35); // 计算斐波那契数列System.out.println("任务" + taskId + "计算结果：" + result + " - 线程：" + Thread.currentThread().getName());});}shutdownGracefully(executor);}private static long fibonacci(int n) {if (n <= 1) return n;return fibonacci(n - 1) + fibonacci(n - 2);}private static void shutdownGracefully(ExecutorService executor) {executor.shutdown();try {if (!executor.awaitTermination(60, TimeUnit.SECONDS)) {executor.shutdownNow();}} catch (InterruptedException e) {executor.shutdownNow();Thread.currentThread().interrupt();}}
}2.2 IO密集型任务线程池
public class IOIntensiveThreadPool {/*** IO密集型任务线程池配置* 核心线程数 = CPU核心数 * 2*/public static ThreadPoolExecutor createIOIntensivePool() {int corePoolSize = Runtime.getRuntime().availableProcessors() * 2;returnnew ThreadPoolExecutor(corePoolSize,corePoolSize * 2,60L,TimeUnit.SECONDS,new LinkedBlockingQueue<>(200),new ThreadFactory() {privatefinal AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread t = new Thread(r, "IO-Pool-" + threadNumber.getAndIncrement());t.setDaemon(false);return t;}},new ThreadPoolExecutor.CallerRunsPolicy());}// 使用示例：文件读写任务public static void main(String[] args) {ThreadPoolExecutor executor = createIOIntensivePool();// 提交IO任务for (int i = 0; i < 20; i++) {finalint taskId = i;executor.submit(() -> {try {// 模拟文件读写操作Thread.sleep(1000); // 模拟IO等待System.out.println("任务" + taskId + "完成文件操作 - 线程：" + Thread.currentThread().getName());} catch (InterruptedException e) {Thread.currentThread().interrupt();}});}shutdownGracefully(executor);}private static void shutdownGracefully(ExecutorService executor) {executor.shutdown();try {if (!executor.awaitTermination(60, TimeUnit.SECONDS)) {executor.shutdownNow();}} catch (InterruptedException e) {executor.shutdownNow();Thread.currentThread().interrupt();}}
}2.3 定时任务线程池
public class ScheduledThreadPoolExample {public static void main(String[] args) throws InterruptedException {ScheduledThreadPoolExecutor scheduler = new ScheduledThreadPoolExecutor(3,new ThreadFactory() {privatefinal AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread t = new Thread(r, "Scheduler-" + threadNumber.getAndIncrement());t.setDaemon(false);return t;}});// 1. 延迟执行任务scheduler.schedule(() -> {System.out.println("延迟3秒执行的任务 - " + new Date());}, 3, TimeUnit.SECONDS);// 2. 固定频率执行任务ScheduledFuture<?> fixedRateTask = scheduler.scheduleAtFixedRate(() -> {System.out.println("每2秒执行一次的任务 - " + new Date());}, 1, 2, TimeUnit.SECONDS);// 3. 固定延迟执行任务ScheduledFuture<?> fixedDelayTask = scheduler.scheduleWithFixedDelay(() -> {System.out.println("上次执行完成后延迟1秒再执行 - " + new Date());try {Thread.sleep(500); // 模拟任务执行时间} catch (InterruptedException e) {Thread.currentThread().interrupt();}}, 1, 1, TimeUnit.SECONDS);// 运行10秒后停止Thread.sleep(10000);fixedRateTask.cancel(false);fixedDelayTask.cancel(false);scheduler.shutdown();}
}3. 线程池监控与管理
3.1 线程池状态监控
public class ThreadPoolMonitor {/*** 创建可监控的线程池*/public static ThreadPoolExecutor createMonitorablePool() {returnnew ThreadPoolExecutor(5, 10, 60L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(100),new ThreadFactory() {privatefinal AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread t = new Thread(r, "Monitor-Pool-" + threadNumber.getAndIncrement());t.setDaemon(false);return t;}},new ThreadPoolExecutor.CallerRunsPolicy()) {@Overrideprotected void beforeExecute(Thread t, Runnable r) {super.beforeExecute(t, r);System.out.println("任务开始执行 - 线程：" + t.getName());}@Overrideprotected void afterExecute(Runnable r, Throwable t) {super.afterExecute(r, t);if (t != null) {System.err.println("任务执行异常：" + t.getMessage());} else {System.out.println("任务执行完成");}}@Overrideprotected void terminated() {super.terminated();System.out.println("线程池已终止");}};}/*** 打印线程池状态信息*/public static void printPoolStatus(ThreadPoolExecutor executor) {System.out.println("\n=== 线程池状态信息 ===");System.out.println("核心线程数：" + executor.getCorePoolSize());System.out.println("最大线程数：" + executor.getMaximumPoolSize());System.out.println("当前线程数：" + executor.getPoolSize());System.out.println("活跃线程数：" + executor.getActiveCount());System.out.println("队列中任务数：" + executor.getQueue().size());System.out.println("已完成任务数：" + executor.getCompletedTaskCount());System.out.println("总任务数：" + executor.getTaskCount());System.out.println("是否关闭：" + executor.isShutdown());System.out.println("是否终止：" + executor.isTerminated());System.out.println("========================\n");}
}3.2 线程池异常处理
public class ThreadPoolExceptionHandling {/*** 创建带异常处理的线程池*/public static ThreadPoolExecutor createSafeThreadPool() {returnnew ThreadPoolExecutor(5, 10, 60L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(50),new ThreadFactory() {privatefinal AtomicInteger threadNumber = new AtomicInteger(1);@Overridepublic Thread newThread(Runnable r) {Thread t = new Thread(r, "Safe-Pool-" + threadNumber.getAndIncrement());t.setDaemon(false);// 设置未捕获异常处理器t.setUncaughtExceptionHandler((thread, ex) -> {System.err.println("线程 " + thread.getName() + " 发生未捕获异常：" + ex.getMessage());ex.printStackTrace();});return t;}},new ThreadPoolExecutor.CallerRunsPolicy());}/*** 安全任务包装器*/public static Runnable wrapTask(Runnable task) {return () -> {try {task.run();} catch (Exception e) {System.err.println("任务执行异常：" + e.getMessage());e.printStackTrace();// 可以在这里添加异常上报逻辑}};}public static void main(String[] args) {ThreadPoolExecutor executor = createSafeThreadPool();// 提交可能抛异常的任务executor.submit(wrapTask(() -> {System.out.println("正常任务执行");}));executor.submit(wrapTask(() -> {thrownew RuntimeException("模拟任务异常");}));// 使用Future处理异常Future<?> future = executor.submit(() -> {thrownew RuntimeException("Future异常");});try {future.get();} catch (ExecutionException e) {System.err.println("通过Future捕获异常：" + e.getCause().getMessage());} catch (InterruptedException e) {Thread.currentThread().interrupt();}executor.shutdown();}
}4. 最佳实践与注意事项
4.1 线程池参数配置指南
public class ThreadPoolConfigGuide {/*** 根据任务类型配置线程池*/publicstaticclass ThreadPoolConfigurator {// CPU密集型任务配置public static ThreadPoolExecutor forCPUIntensive() {int processors = Runtime.getRuntime().availableProcessors();returnnew ThreadPoolExecutor(processors, // 核心线程数 = CPU核心数processors, // 最大线程数 = CPU核心数0L, TimeUnit.MILLISECONDS, // 无空闲时间new ArrayBlockingQueue<>(processors * 2), // 队列大小适中new ThreadPoolExecutor.AbortPolicy());}// IO密集型任务配置public static ThreadPoolExecutor forIOIntensive() {int processors = Runtime.getRuntime().availableProcessors();returnnew ThreadPoolExecutor(processors * 2, // 核心线程数 = CPU核心数 * 2processors * 4, // 最大线程数 = CPU核心数 * 460L, TimeUnit.SECONDS, // 空闲60秒回收new LinkedBlockingQueue<>(1000), // 较大的队列new ThreadPoolExecutor.CallerRunsPolicy());}// 混合型任务配置public static ThreadPoolExecutor forMixed() {int processors = Runtime.getRuntime().availableProcessors();returnnew ThreadPoolExecutor(processors + 1, // 核心线程数 = CPU核心数 + 1processors * 2, // 最大线程数 = CPU核心数 * 260L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(200),new ThreadPoolExecutor.CallerRunsPolicy());}}
}4.2 常见问题与解决方案
public class ThreadPoolTroubleshooting {/*** 问题1：线程池任务积压* 解决方案：动态调整线程池大小*/publicstaticclass DynamicThreadPool {privatefinal ThreadPoolExecutor executor;privatefinal ScheduledExecutorService monitor;public DynamicThreadPool(ThreadPoolExecutor executor) {this.executor = executor;this.monitor = Executors.newSingleThreadScheduledExecutor();startMonitoring();}private void startMonitoring() {monitor.scheduleAtFixedRate(() -> {int queueSize = executor.getQueue().size();int activeCount = executor.getActiveCount();int corePoolSize = executor.getCorePoolSize();int maxPoolSize = executor.getMaximumPoolSize();// 队列积压严重，增加线程if (queueSize > 100 && activeCount >= corePoolSize * 0.8) {int newCoreSize = Math.min(corePoolSize + 1, maxPoolSize);if (newCoreSize > corePoolSize) {executor.setCorePoolSize(newCoreSize);System.out.println("增加核心线程数至：" + newCoreSize);}}// 队列空闲，减少线程if (queueSize < 10 && activeCount < corePoolSize * 0.5 && corePoolSize > 2) {executor.setCorePoolSize(corePoolSize - 1);System.out.println("减少核心线程数至：" + (corePoolSize - 1));}}, 0, 30, TimeUnit.SECONDS);}}/*** 问题2：任务执行时间过长* 解决方案：任务超时控制*/publicstaticclass TimeoutTaskExecutor {privatefinal ThreadPoolExecutor executor;public TimeoutTaskExecutor(ThreadPoolExecutor executor) {this.executor = executor;}public <T> T executeWithTimeout(Callable<T> task, long timeout, TimeUnit unit) throws InterruptedException, ExecutionException, TimeoutException {Future<T> future = executor.submit(task);try {return future.get(timeout, unit);} catch (TimeoutException e) {future.cancel(true); // 取消任务throw e;}}}
}4.3 性能优化建议
线程池性能优化清单：1. 参数配置优化✓ 根据任务类型选择合适的核心线程数✓ 设置合理的最大线程数和队列大小✓ 选择适当的拒绝策略2. 任务设计优化✓ 避免任务执行时间过长✓ 合理拆分大任务✓ 避免任务间的强依赖关系3. 监控与调优✓ 定期监控线程池状态✓ 记录任务执行时间✓ 根据监控数据调整参数4. 资源管理✓ 及时关闭线程池✓ 避免创建过多线程池✓ 合理设置线程优先级5. 总结
Java线程池是并发编程的重要工具，正确使用线程池可以：
提高性能：减少线程创建和销毁的开销
控制资源：限制并发线程数量，避免系统资源耗尽
提高响应性：复用线程，快速响应任务请求
便于管理：统一管理线程生命周期
关键要点：
避免使用
Executors创建线程池，推荐手动创建ThreadPoolExecutor根据任务类型（CPU密集型/IO密集型）合理配置参数
实施有效的监控和异常处理机制
注意线程池的优雅关闭
定期评估和调优线程池配置
通过遵循这些最佳实践，可以充分发挥线程池的优势，构建高性能、稳定的并发应用程序。
通过指针引用数组)
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