- @Slf4j(topic = "c.TestPool")
- public class TestPool {
-
- public static void main(String[] args) {
- ThreadPool threadPool = new ThreadPool(2,
- 1000, TimeUnit.MILLISECONDS, 10);
- for (int i = 0; i < 5; i++) {
- int j =i;
- threadPool.execute(() -> {
- log.debug("{}",j);
- });
- }
- }
-
- }
-
- @Slf4j(topic = "c.ThreadPool")
- class ThreadPool {
- // 任务队列
- private BlockingQueue
taskQueue; -
- // 线程集合
- private HashSet
workers = new HashSet<>(); -
- // 核心线程数
- private int coreSize;
-
- // 获取任务时的超时时间
- private long timeout;
-
- private TimeUnit timeUnit;
-
- public ThreadPool(int coreSize, long timeout, TimeUnit timeUnit, int queueCapcity) {
- this.coreSize = coreSize;
- this.timeout = timeout;
- this.timeUnit = timeUnit;
- this.taskQueue = new BlockingQueue<>(queueCapcity);
- }
-
- // 执行任务
- public void execute(Runnable task) {
- // 当任务数没有超过 coreSize 时,直接交给 worker 对象执行
- // 如果任务数超过 coreSize 时,加入任务队列暂存
- synchronized (workers) {
- if (workers.size() < coreSize) {
- Worker worker = new Worker(task);
- log.debug("新增 worker{}, {}", worker, task);
- workers.add(worker);
- worker.start();
- } else {
- taskQueue.put(task);
- }
- }
-
- }
-
-
- class Worker extends Thread {
- private Runnable task;
-
- public Worker(Runnable task) {
- this.task = task;
- }
-
- @Override
- public void run() {
- // 执行任务
- // 1) 当 task 不为空,执行任务
- // 2) 当 task 执行完毕,再接着从任务队列获取任务并执行
- // while (task != null || (task = taskQueue.take()) != null) {
- while(task != null || (task = taskQueue.poll(timeout, timeUnit)) != null) {
- try {
-
- log.debug("正在执行...{}", task);
- task.run();
- } catch (Exception e) {
- e.printStackTrace();
- } finally {
- task = null;
- }
- }
- synchronized (workers) {
- log.debug("worker 被移除{}", this);
- workers.remove(this);
- }
-
- }
- }
- }
-
- // 阻塞队列
- @Slf4j(topic = "c.BlockingQueue")
- class BlockingQueue
{ - // 1. 任务队列
- private Deque
queue = new ArrayDeque<>(); -
- // 2. 锁
- private ReentrantLock lock = new ReentrantLock();
-
- // 3. 生产者条件变量
- private Condition fullWaitSet = lock.newCondition();
-
- // 4. 消费者条件变量
- private Condition emptyWaitSet = lock.newCondition();
-
- // 5. 容量
- private int capcity;
-
- public BlockingQueue(int capcity) {
- this.capcity = capcity;
- }
-
- // 带超时阻塞获取
- public T poll(long timeout, TimeUnit unit) {
- lock.lock();
- try {
- // 将 timeout 统一转换为 纳秒
- long nanos = unit.toNanos(timeout);
- while (queue.isEmpty()) {
- try {
- if (nanos <= 0) {
- return null;
- }
- // 返回值是剩余时间
- nanos = emptyWaitSet.awaitNanos(nanos);
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- T t = queue.removeFirst();
- fullWaitSet.signal();
- return t;
- } finally {
- lock.unlock();
- }
- }
-
- // 阻塞获取
- public T take() {
- lock.lock();
- try {
- while (queue.isEmpty()) {
- try {
- emptyWaitSet.await();
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- T t = queue.removeFirst();
- fullWaitSet.signal();
- return t;
- } finally {
- lock.unlock();
- }
- }
-
- // 阻塞添加
- public void put(T task) {
- lock.lock();
- try {
- while (queue.size() == capcity) {
- try {
- log.debug("等待加入任务队列 {} ...", task);
- fullWaitSet.await();
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- log.debug("加入任务队列 {}", task);
- queue.addLast(task);
- emptyWaitSet.signal();
- } finally {
- lock.unlock();
- }
- }
-
- public int size() {
- lock.lock();
- try {
- return queue.size();
- } finally {
- lock.unlock();
- }
- }
- }
- @Slf4j(topic = "c.TestPool")
- public class TestPool {
- public static void main(String[] args) {
- ThreadPool threadPool = new ThreadPool(1,
- 1000, TimeUnit.MILLISECONDS, 1, (queue, task)->{
- // 1. 死等
- // queue.put(task);
- // 2) 带超时等待
- // queue.offer(task, 1500, TimeUnit.MILLISECONDS);
- // 3) 让调用者放弃任务执行
- // log.debug("放弃{}", task);
- // 4) 让调用者抛出异常
- // throw new RuntimeException("任务执行失败 " + task);
- // 5) 让调用者自己执行任务
- task.run();
- });
- for (int i = 0; i < 4; i++) {
- int j = i;
- threadPool.execute(() -> {
- try {
- Thread.sleep(1000L);
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- log.debug("{}", j);
- });
- }
- }
- }
-
- @FunctionalInterface // 拒绝策略
- interface RejectPolicy
{ - void reject(BlockingQueue
queue, T task) ; - }
-
- @Slf4j(topic = "c.ThreadPool")
- class ThreadPool {
- // 任务队列
- private BlockingQueue
taskQueue; -
- // 线程集合
- private HashSet
workers = new HashSet<>(); -
- // 核心线程数
- private int coreSize;
-
- // 获取任务时的超时时间
- private long timeout;
-
- private TimeUnit timeUnit;
-
- private RejectPolicy
rejectPolicy; -
- // 执行任务
- public void execute(Runnable task) {
- // 当任务数没有超过 coreSize 时,直接交给 worker 对象执行
- // 如果任务数超过 coreSize 时,加入任务队列暂存
- synchronized (workers) {
- if(workers.size() < coreSize) {
- Worker worker = new Worker(task);
- log.debug("新增 worker{}, {}", worker, task);
- workers.add(worker);
- worker.start();
- } else {
- // taskQueue.put(task);
- // 1) 死等
- // 2) 带超时等待
- // 3) 让调用者放弃任务执行
- // 4) 让调用者抛出异常
- // 5) 让调用者自己执行任务
- taskQueue.tryPut(rejectPolicy, task);
- }
- }
- }
-
- public ThreadPool(int coreSize, long timeout, TimeUnit timeUnit, int queueCapcity, RejectPolicy
rejectPolicy) { - this.coreSize = coreSize;
- this.timeout = timeout;
- this.timeUnit = timeUnit;
- this.taskQueue = new BlockingQueue<>(queueCapcity);
- this.rejectPolicy = rejectPolicy;
- }
-
- class Worker extends Thread{
- private Runnable task;
-
- public Worker(Runnable task) {
- this.task = task;
- }
-
- @Override
- public void run() {
- // 执行任务
- // 1) 当 task 不为空,执行任务
- // 2) 当 task 执行完毕,再接着从任务队列获取任务并执行
- // while(task != null || (task = taskQueue.take()) != null) {
- while(task != null || (task = taskQueue.poll(timeout, timeUnit)) != null) {
- try {
- log.debug("正在执行...{}", task);
- task.run();
- } catch (Exception e) {
- e.printStackTrace();
- } finally {
- task = null;
- }
- }
- synchronized (workers) {
- log.debug("worker 被移除{}", this);
- workers.remove(this);
- }
- }
- }
- }
- @Slf4j(topic = "c.BlockingQueue")
- class BlockingQueue
{ - // 1. 任务队列
- private Deque
queue = new ArrayDeque<>(); -
- // 2. 锁
- private ReentrantLock lock = new ReentrantLock();
-
- // 3. 生产者条件变量
- private Condition fullWaitSet = lock.newCondition();
-
- // 4. 消费者条件变量
- private Condition emptyWaitSet = lock.newCondition();
-
- // 5. 容量
- private int capcity;
-
- public BlockingQueue(int capcity) {
- this.capcity = capcity;
- }
-
- // 带超时阻塞获取
- public T poll(long timeout, TimeUnit unit) {
- lock.lock();
- try {
- // 将 timeout 统一转换为 纳秒
- long nanos = unit.toNanos(timeout);
- while (queue.isEmpty()) {
- try {
- // 返回值是剩余时间
- if (nanos <= 0) {
- return null;
- }
- nanos = emptyWaitSet.awaitNanos(nanos);
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- T t = queue.removeFirst();
- fullWaitSet.signal();
- return t;
- } finally {
- lock.unlock();
- }
- }
-
- // 阻塞获取
- public T take() {
- lock.lock();
- try {
- while (queue.isEmpty()) {
- try {
- emptyWaitSet.await();
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- T t = queue.removeFirst();
- fullWaitSet.signal();
- return t;
- } finally {
- lock.unlock();
- }
- }
-
- // 阻塞添加
- public void put(T task) {
- lock.lock();
- try {
- while (queue.size() == capcity) {
- try {
- log.debug("等待加入任务队列 {} ...", task);
- fullWaitSet.await();
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- log.debug("加入任务队列 {}", task);
- queue.addLast(task);
- emptyWaitSet.signal();
- } finally {
- lock.unlock();
- }
- }
-
- // 带超时时间阻塞添加
- public boolean offer(T task, long timeout, TimeUnit timeUnit) {
- lock.lock();
- try {
- long nanos = timeUnit.toNanos(timeout);
- while (queue.size() == capcity) {
- try {
- if(nanos <= 0) {
- return false;
- }
- log.debug("等待加入任务队列 {} ...", task);
- nanos = fullWaitSet.awaitNanos(nanos);
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- log.debug("加入任务队列 {}", task);
- queue.addLast(task);
- emptyWaitSet.signal();
- return true;
- } finally {
- lock.unlock();
- }
- }
-
- public int size() {
- lock.lock();
- try {
- return queue.size();
- } finally {
- lock.unlock();
- }
- }
-
- public void tryPut(RejectPolicy
rejectPolicy, T task) { - lock.lock();
- try {
- // 判断队列是否满
- if(queue.size() == capcity) {
- rejectPolicy.reject(this, task);
- } else { // 有空闲
- log.debug("加入任务队列 {}", task);
- queue.addLast(task);
- emptyWaitSet.signal();
- }
- } finally {
- lock.unlock();
- }
- }
- }
ThreadPoolExecutor 使用 int 的 高 3 位来表示线程池状态,低 29 位表示线程数量![]()
从数字上比较,TERMINATED > TIDYING > STOP > SHUTDOWN > RUNNING
这些信息存储在一个原子变量 ctl 中,目的是将线程池状态与线程个数合二为一,这样就可以用一次 cas 原子操作进行赋值![]()
public ThreadPoolExecutor(int corePoolSize, int maximumPoolSize, long keepAliveTime, TimeUnit unit, BlockingQueueworkQueue, ThreadFactory threadFactory, RejectedExecutionHandler handler)(1)corePoolSize 核心线程数目 ( 最多保留的线程数 )(2)maximumPoolSize 最大线程数目(3)keepAliveTime 生存时间 - 针对救急线程(4)unit 时间单位 - 针对救急线程(5)workQueue 阻塞队列(6)threadFactory 线程工厂 - 可以为线程创建时起个好名字(7)handler 拒绝策略
工作方式:
(1)线程池中刚开始没有线程,当一个任务提交给线程池后,线程池会创建一个新线程来执行任务。
(2)当线程数达到 corePoolSize 并没有线程空闲,这时再加入任务,新加的任务会被加入 workQueue 队列排队,直到有空闲的线程。(3)如果队列选择了有界队列,那么任务超过了队列大小时,会创建 maximumPoolSize - corePoolSize 数目的线程来救急。(4)如果线程到达 maximumPoolSize 仍然有新任务这时会执行拒绝策略。拒绝策略 jdk 提供了 4 种实现,其它著名框架也提供了实现1️⃣AbortPolicy 让调用者抛出 RejectedExecutionException 异常,这是 默认策略2️⃣CallerRunsPolicy 让调用者运行任务3️⃣DiscardPolicy 放弃本次任务4️⃣DiscardOldestPolicy 放弃队列中最早的任务,本任务取而代之5️⃣Dubbo 的实现,在抛出 RejectedExecutionException 异常之前会记录日志,并 dump 线程栈信息,方便定位问题6️⃣Netty 的实现,是创建一个新线程来执行任务7️⃣ActiveMQ 的实现,带超时等待( 60s )尝试放入队列,类似我们之前自定义的拒绝策略8️⃣PinPoint 的实现,它使用了一个拒绝策略链,会逐一尝试策略链中每种拒绝策略(5) 当高峰过去后,超过 corePoolSize 的救急线程如果一段时间没有任务做,需要结束节省资源,这个时间由 keepAliveTime 和 unit 来控制。
拒绝策略
根据这个构造方法, JDK Executors 类中提供了众多工厂方法来创建各种用途的线程池
public static ExecutorService newFixedThreadPool(int nThreads) { return new ThreadPoolExecutor(nThreads, nThreads, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue()); }特点:(1)核心线程数 == 最大线程数(没有救急线程被创建),因此也无需超时时间(2)阻塞队列是无界的,可以放任意数量的任务
评价 适用于任务量已知,相对耗时的任务
public class TestThreadPoolExecutors { public static void main(String[] args) { ExecutorService pool = Executors.newFixedThreadPool(2); ExecutorService pool2 = Executors.newFixedThreadPool(2, new ThreadFactory() { private AtomicInteger t = new AtomicInteger(1); @Override public Thread newThread(Runnable r) { return new Thread(r, "mypool_t" + t.getAndIncrement()); } }); pool.execute(() -> { log.debug("1"); }); pool.execute(() -> { log.debug("1"); }); pool.execute(() -> { log.debug("1"); }); } }
public static ExecutorService newCachedThreadPool() { return new ThreadPoolExecutor(0, Integer.MAX_VALUE, 60L, TimeUnit.SECONDS, new SynchronousQueue()); }特点:(1) 核心线程数是 0, 最大线程数是 Integer.MAX_VALUE ,救急线程的空闲生存时间是 60s ,意味着1️⃣全部都是救急线程( 60s 后可以回收)2️⃣ 救急线程可以无限创建(2) 队列采用了 SynchronousQueue 实现特点是,它没有容量,没有线程来取是放不进去的(一手交钱、一手交 货)
@Slf4j(topic = "c.TestSynchronousQueue") public class TestSynchronousQueue { public static void main(String[] args) { SynchronousQueueintegers = new SynchronousQueue<>(); new Thread(() -> { try { log.debug("putting {} ", 1); integers.put(1); log.debug("{} putted...", 1); log.debug("putting...{} ", 2); integers.put(2); log.debug("{} putted...", 2); } catch (InterruptedException e) { e.printStackTrace(); } },"t1").start(); sleep(1); new Thread(() -> { try { log.debug("taking {}", 1); integers.take(); } catch (InterruptedException e) { e.printStackTrace(); } },"t2").start(); sleep(1); new Thread(() -> { try { log.debug("taking {}", 2); integers.take(); } catch (InterruptedException e) { e.printStackTrace(); } },"t3").start(); } }![]()
评价
(1)整个线程池表现为线程数会根据任务量不断增长,没有上限,当任务执行完毕,空闲 1分钟后释放线程。(2)适合任务数比较密集,但每个任务执行时间较短的情况
public static ExecutorService newSingleThreadExecutor() { return new FinalizableDelegatedExecutorService (new ThreadPoolExecutor(1, 1, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue())); }使用场景:希望多个任务排队执行。线程数固定为 1 ,任务数多于 1 时,会放入无界队列排队。任务执行完毕,这唯一的线程也不会被释放。
区别:(1) 自己创建一个单线程串行执行任务,如果任务执行失败而终止那么没有任何补救措施,而线程池还会新建一个线程,保证池的正常工作(2) Executors.newSingleThreadExecutor() 线程个数始终为 1 ,不能修改1️⃣FinalizableDelegatedExecutorService 应用的是装饰器模式,只对外暴露了 ExecutorService 接口,因此不能调用 ThreadPoolExecutor 中特有的方法(3) Executors.newFixedThreadPool(1) 初始时为 1 ,以后还可以修改1️⃣ 对外暴露的是 ThreadPoolExecutor 对象,可以强转后调用 setCorePoolSize 等方法进行修改
@Slf4j(topic = "c.TestExecutors") public class TestExecutors { public static void main(String[] args) throws InterruptedException { test2(); } public static void test2() { ExecutorService pool = Executors.newSingleThreadExecutor(); pool.execute(() -> { log.debug("1"); int i = 1 / 0; log.debug("111"); }); pool.execute(() -> { log.debug("2"); }); pool.execute(() -> { log.debug("3"); }); } }
- // 执行任务
- void execute(Runnable command);
-
- // 提交任务 task,用返回值 Future 获得任务执行结果
-
Future submit(Callable task) ; -
- // 提交 tasks 中所有任务
-
List> invokeAll(Collection extends Callable> tasks) - throws InterruptedException;
-
- // 提交 tasks 中所有任务,带超时时间
-
List> invokeAll(Collection extends Callable> tasks, - long timeout, TimeUnit unit)
- throws InterruptedException;
-
- // 提交 tasks 中所有任务,哪个任务先成功执行完毕,返回此任务执行结果,其它任务取消
-
T invokeAny(Collection extends Callable> tasks) - throws InterruptedException, ExecutionException;
-
- // 提交 tasks 中所有任务,哪个任务先成功执行完毕,返回此任务执行结果,其它任务取消,带超时时间
-
T invokeAny(Collection extends Callable> tasks, - long timeout, TimeUnit unit)
- throws InterruptedException, ExecutionException, TimeoutException;
- }
- @Slf4j(topic = "c.TestSubmit")
- public class TestSubmit {
-
- public static void main(String[] args) throws ExecutionException, InterruptedException {
- ExecutorService pool = Executors.newFixedThreadPool(1);
-
- }
-
- private static void method3(ExecutorService pool) throws InterruptedException, ExecutionException {
- String result = pool.invokeAny(Arrays.asList(
- () -> {
- log.debug("begin 1");
- Thread.sleep(1000);
- log.debug("end 1");
- return "1";
- },
- () -> {
- log.debug("begin 2");
- Thread.sleep(500);
- log.debug("end 2");
- return "2";
- },
- () -> {
- log.debug("begin 3");
- Thread.sleep(2000);
- log.debug("end 3");
- return "3";
- }
- ));
- log.debug("{}", result);
- }
-
- private static void method2(ExecutorService pool) throws InterruptedException {
- List
> futures = pool.invokeAll(Arrays.asList( - () -> {
- log.debug("begin");
- Thread.sleep(1000);
- return "1";
- },
- () -> {
- log.debug("begin");
- Thread.sleep(500);
- return "2";
- },
- () -> {
- log.debug("begin");
- Thread.sleep(2000);
- return "3";
- }
- ));
-
- futures.forEach( f -> {
- try {
- log.debug("{}", f.get());
- } catch (InterruptedException | ExecutionException e) {
- e.printStackTrace();
- }
- });
- }
-
- private static void method1(ExecutorService pool) throws InterruptedException, ExecutionException {
- // new Callable<>()
- Future
future = pool.submit(() -> { - log.debug("running");
- Thread.sleep(1000);
- return "ok";
- });
-
- log.debug("{}", future.get());
- }
- }
/* 线程池状态变为 SHUTDOWN - 不会接收新任务 - 但已提交任务会执行完 - 此方法不会阻塞调用线程的执行 */ void shutdown();
public void shutdown() { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { checkShutdownAccess(); // 修改线程池状态 advanceRunState(SHUTDOWN); // 仅会打断空闲线程 interruptIdleWorkers(); onShutdown(); // 扩展点 ScheduledThreadPoolExecutor } finally { mainLock.unlock(); } // 尝试终结(没有运行的线程可以立刻终结,如果还有运行的线程也不会等) tryTerminate(); }
/* 线程池状态变为 STOP - 不会接收新任务 - 会将队列中的任务返回 - 并用 interrupt 的方式中断正在执行的任务 */ ListshutdownNow();
public ListshutdownNow() {List tasks; final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { checkShutdownAccess(); // 修改线程池状态 advanceRunState(STOP); // 打断所有线程 interruptWorkers(); // 获取队列中剩余任务 tasks = drainQueue(); } finally { mainLock.unlock(); } // 尝试终结 tryTerminate(); return tasks; }
- // 不在 RUNNING 状态的线程池,此方法就返回 true
- boolean isShutdown();
- // 线程池状态是否是 TERMINATED
- boolean isTerminated();
- // 调用 shutdown 后,由于调用线程并不会等待所有任务运行结束,因此如果它想在线程池 TERMINATED 后做些事情,可以利用此方法等待
- boolean awaitTermination(long timeout, TimeUnit unit) throws InterruptedException;
- @Slf4j(topic = "c.TestShutDown")
- public class TestShutDown {
-
- public static void main(String[] args) throws ExecutionException, InterruptedException {
- ExecutorService pool = Executors.newFixedThreadPool(2);
-
- Future
result1 = pool.submit(() -> { - log.debug("task 1 running...");
- Thread.sleep(1000);
- log.debug("task 1 finish...");
- return 1;
- });
-
- Future
result2 = pool.submit(() -> { - log.debug("task 2 running...");
- Thread.sleep(1000);
- log.debug("task 2 finish...");
- return 2;
- });
-
- Future
result3 = pool.submit(() -> { - log.debug("task 3 running...");
- Thread.sleep(1000);
- log.debug("task 3 finish...");
- return 3;
- });
-
- log.debug("shutdown");
- // pool.shutdown();
- // pool.awaitTermination(3, TimeUnit.SECONDS);
- List
runnables = pool.shutdownNow(); - log.debug("other.... {}" , runnables);
- }
- }
让有限的工作线程( Worker Thread)来轮流异步处理无限多的任务。也可以将其归类为分工模式,它的典型实现就是线程池,也体现了经典设计模式中的享元模式。
例如,海底捞的服务员(线程),轮流处理每位客人的点餐(任务),如果为每位客人都配一名专属的服务员,那么成本就太高了(对比另一种多线程设计模式: Thread-Per-Message )注意,不同任务类型应该使用不同的线程池,这样能够避免饥饿,并能提升效率例如,如果一个餐馆的工人既要招呼客人(任务类型 A ),又要到后厨做菜(任务类型 B)显然效率不咋地,分成服务员(线程池 A )与厨师(线程池 B )更为合理,当然你能想到更细致的分工
固定大小线程池会有饥饿现象
两个工人是同一个线程池中的两个线程他们要做的事情是:为客人点餐和到后厨做菜,这是两个阶段的工作比如工人 A 处理了点餐任务,接下来它要等着 工人 B 把菜做好,然后上菜,他俩也配合的蛮好但现在同时来了两个客人,这个时候工人 A 和工人 B 都去处理点餐了,这时没人做饭了,饥饿
@Slf4j(topic = "c.TestDeadLock") public class TestStarvation { static final ListMENU = Arrays.asList("地三鲜", "宫保鸡丁", "辣子鸡丁", "烤鸡翅"); static Random RANDOM = new Random(); static String cooking() { return MENU.get(RANDOM.nextInt(MENU.size())); } public static void main(String[] args) { ExecutorService waiterPool = Executors.newFixedThreadPool(1); ExecutorService cookPool = Executors.newFixedThreadPool(1); waiterPool.execute(() -> { log.debug("处理点餐..."); Futuref = cookPool.submit(() -> { log.debug("做菜"); return cooking(); }); try { log.debug("上菜: {}", f.get()); } catch (InterruptedException | ExecutionException e) { e.printStackTrace(); } }); waiterPool.execute(() -> { log.debug("处理点餐..."); Futuref = cookPool.submit(() -> { log.debug("做菜"); return cooking(); }); try { log.debug("上菜: {}", f.get()); } catch (InterruptedException | ExecutionException e) { e.printStackTrace(); } }); } }解决方法可以增加线程池的大小,不过不是根本解决方案,还是前面提到的, 不同的任务类型,采用不同的线程池
过小会导致程序不能充分地利用系统资源、容易导致饥饿过大会导致更多的线程上下文切换,占用更多内存
(1)CPU 密集型运算
通常采用 cpu 核数 + 1 能够实现最优的 CPU 利用率, +1 是保证当线程由于页缺失故障(操作系统)或其它原因导致暂停时,额外的这个线程就能顶上去,保证 CPU 时钟周期不被浪费
(2)I/O 密集型运算
CPU 不总是处于繁忙状态,例如,当你执行业务计算时,这时候会使用 CPU 资源,但当你执行 I/O 操作时、远程RPC 调用时,包括进行数据库操作时,这时候 CPU 就闲下来了,你可以利用多线程提高它的利用率。![]()
在『 任务调度线程池 』功能加入之前,可以使用 java.util.Timer 来实现定时功能,Timer 的优点在于简单易用,但由于所有任务都是由同一个线程来调度,因此所有任务都是串行执行的,同一时间只能有一个任务在执行,前一个任务的延迟或异常都将会影响到之后的任务。
@Slf4j(topic = "c.TestTimer") public class TestTimer { public static void main(String[] args) throws ExecutionException, InterruptedException { /*ScheduledExecutorService pool = Executors.newScheduledThreadPool(1); pool.schedule(() -> { try { log.debug("task1"); int i = 1 / 0; } catch (Exception e) { log.error("error:", e); } }, 1, TimeUnit.SECONDS);*/ ExecutorService pool = Executors.newFixedThreadPool(1); pool.submit(() -> { try { log.debug("task1"); int i = 1 / 0; } catch (Exception e) { log.error("error:", e); } }); } private static void method3() { ScheduledExecutorService pool = Executors.newScheduledThreadPool(1); log.debug("start..."); pool.scheduleAtFixedRate(() -> { log.debug("running..."); }, 1, 1, TimeUnit.SECONDS); } private static void method2(ScheduledExecutorService pool) { pool.schedule(() -> { log.debug("task1"); int i = 1 / 0; }, 1, TimeUnit.SECONDS); pool.schedule(() -> { log.debug("task2"); }, 1, TimeUnit.SECONDS); } private static void method1() { Timer timer = new Timer(); TimerTask task1 = new TimerTask() { @Override public void run() { log.debug("task 1"); sleep(2); } }; TimerTask task2 = new TimerTask() { @Override public void run() { log.debug("task 2"); } }; log.debug("start..."); timer.schedule(task1, 1000); timer.schedule(task2, 1000); } }
- public class TestSchedule {
-
- // 如何让每周四 18:00:00 定时执行任务?
- public static void main(String[] args) {
- // 获取当前时间
- LocalDateTime now = LocalDateTime.now();
- System.out.println(now);
- // 获取周四时间
- LocalDateTime time = now.withHour(18).withMinute(0).withSecond(0).withNano(0).with(DayOfWeek.THURSDAY);
- // 如果 当前时间 > 本周周四,必须找到下周周四
- if(now.compareTo(time) > 0) {
- time = time.plusWeeks(1);
- }
- System.out.println(time);
- // initailDelay 代表当前时间和周四的时间差
- // period 一周的间隔时间
- long initailDelay = Duration.between(now, time).toMillis();
- long period = 1000 * 60 * 60 * 24 * 7;
- ScheduledExecutorService pool = Executors.newScheduledThreadPool(1);
- pool.scheduleAtFixedRate(() -> {
- System.out.println("running...");
- }, initailDelay, period, TimeUnit.MILLISECONDS);
- }
- }
Fork/Join 是 JDK 1.7 加入的新的线程池实现,它体现的是一种分治思想,适用于能够进行任务拆分的 cpu 密集型运算
所谓的任务拆分,是将一个大任务拆分为算法上相同的小任务,直至不能拆分可以直接求解。跟递归相关的一些计算,如归并排序、斐波那契数列、都可以用分治思想进行求解
Fork/Join 在分治的基础上加入了多线程,可以把每个任务的分解和合并交给不同的线程来完成,进一步提升了运算效率
Fork/Join 默认会创建与 cpu 核心数大小相同的线程池
提交给 Fork/Join 线程池的任务需要继承 RecursiveTask(有返回值)或 RecursiveAction(没有返回值),例如下面定义了一个对 1~n 之间的整数求和的任务
public class TestForkJoin { public static void main(String[] args) { ForkJoinPool pool = new ForkJoinPool(4); System.out.println(pool.invoke(new AddTask1(5))); } } @Slf4j(topic = "c.AddTask") class AddTask1 extends RecursiveTask{ int n; public AddTask1(int n) { this.n = n; } @Override public String toString() { return "{" + n + '}'; } @Override protected Integer compute() { if (n == 1) { log.debug("join() {}", n); return n; } AddTask1 t1 = new AddTask1(n - 1); t1.fork(); log.debug("fork() {} + {}", n, t1); int result = n + t1.join(); log.debug("join() {} + {} = {}", n, t1, result); return result; } }
public class TestForkJoin { public static void main(String[] args) { ForkJoinPool pool = new ForkJoinPool(4); System.out.println(pool.invoke(new AddTask3(1, 5))); } } @Slf4j(topic = "c.AddTask") class AddTask3 extends RecursiveTask{ int begin; int end; public AddTask3(int begin, int end) { this.begin = begin; this.end = end; } @Override public String toString() { return "{" + begin + "," + end + '}'; } @Override protected Integer compute() { if (begin == end) { log.debug("join() {}", begin); return begin; } if (end - begin == 1) { log.debug("join() {} + {} = {}", begin, end, end + begin); return end + begin; } int mid = (end + begin) / 2; AddTask3 t1 = new AddTask3(begin, mid); t1.fork(); AddTask3 t2 = new AddTask3(mid + 1, end); t2.fork(); log.debug("fork() {} + {} = ?", t1, t2); int result = t1.join() + t2.join(); log.debug("join() {} + {} = {}", t1, t2, result); return result; } }