1. Callable
有两种创建线程的方法-一种是通过创建Thread类,另一种是通过使用Runnable创建线程。但是,Runnable缺少的一项功能是,当线程终止时(即run() 完成时),我们无法使线程返回结果。为了支持此功能,Java中提供了Callable接口。
- 为了实现Runnable,需要实现不返回任何内容的run() 方法,而对于
Callable
,需要实现在完成时返回结果的call() 方法。请注意,不能使用Callable创建线程,只能使用Runnable创建线程。 - 另一个区别是call() 方法可以引发异常,而run() 则不能。
- 为实现Callable而必须重写call方法。
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.SneakyThrows;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Date;
import java.util.List;
import java.util.Random;
import java.util.concurrent.*;
/**
* 启动11个线程, 10个线程计算从0至100的累加和,第11个线程计算10个线程的结果和并输出。
* 请使用Callable和Thread分别实现
*/
public class CallableAndThread {
public static void main(String[] args) throws InterruptedException, ExecutionException {
System.out.println(new CallableExample().test());
System.out.println(new ThreadExample().test());
}
}
/**
* CallableExample
*/
class CallableExample{
/**
* 使用Executors.newFixedThreadPool创建线程池
* @return
* @throws ExecutionException
* @throws InterruptedException
*/
public int test() throws ExecutionException, InterruptedException {
//线程池内线程数量
int TASK_COUNT = 10;
//线程池存储线程
ExecutorService pool = Executors.newFixedThreadPool(TASK_COUNT);
//结果集收集结果
List<Future<Integer>> resultFutureList = new ArrayList<Future<Integer>>();
//执行线程,收集结果
for (int i = 0; i < TASK_COUNT; i++) {
MyCallable myCallable = new MyCallable("线程"+i);
Future<Integer> future = pool.submit(myCallable);
resultFutureList.add(future);
}
//计算总和
Future<Integer> sumFuture =pool.submit(new Callable<Integer>() {
@Override
public Integer call() throws Exception {
int sum = 0;
for (int i = 0; i < TASK_COUNT; sum += resultFutureList.get(i).get(), i++);
return sum;
}
});
//线程池关闭
pool.shutdown();
return sumFuture.get();
}
/**
* 实现Callable接口
*/
@Data
@AllArgsConstructor
@NoArgsConstructor
private static class MyCallable implements Callable<Integer>{
//线程名称
private String threadName;
@Override
public Integer call() throws Exception {
Random random = new Random();
int sleepTimes = random.nextInt(10);
System.out.println(threadName+"睡眠"+sleepTimes+"秒..., 当前时间"+ new SimpleDateFormat("HH:mm:ss").format(new Date()));
TimeUnit.SECONDS.sleep(sleepTimes);
Integer sum = 0;
for (int i = 0; i <= 100; sum += i, i++);
System.out.println(threadName+"计算结果"+sum+",完成时间:"+new SimpleDateFormat("HH:mm:ss").format(new Date()));
return sum;
}
}
}
/**
* ThreadExample
*/
class ThreadExample{
/**
* 线程直接使用new Thread来创建
* @return
*/
public int test() throws InterruptedException {
int THREAD_COUNT = 10;
MyRunnable[] myRunnables = new MyRunnable[THREAD_COUNT];
for (int i = 0; i < THREAD_COUNT; i++) {
myRunnables[i] = new MyRunnable();
new Thread(myRunnables[i],"线程"+i).start();
}
//收集结果
int sum = 0;
for (int i = 0; i < THREAD_COUNT; sum += myRunnables[i].get().intValue(), i++);
return sum;
}
/**
* 实现Runnable
*/
@Data
public static class MyRunnable implements Runnable{
private Integer sum = 0;
@SneakyThrows
@Override
public void run() {
Random random = new Random();
int sleepTimes = random.nextInt(10);
System.out.println(Thread.currentThread().getName()+"睡眠"+sleepTimes+"秒..., 当前时间"+ new SimpleDateFormat("HH:mm:ss").format(new Date()));
TimeUnit.SECONDS.sleep(sleepTimes);
for (int i = 0; i <= 100; this.sum += i, i++);
System.out.println(Thread.currentThread().getName()+"计算结果"+sum+",完成时间:"+new SimpleDateFormat("HH:mm:ss").format(new Date()));
//唤醒其他线程
synchronized(this){
notifyAll();
}
}
/**
* 同步方法获取结果值
* @return
* @throws InterruptedException
*/
public synchronized Integer get() throws InterruptedException {
while (this.sum == 0){
wait();
}
return this.sum;
}
}
}
Callable 与Thread的区别:
- 最大的区别是Callable有返回值,而Thread没有。
- Callable必须配合线程池和Future类使用。Thread不需要,它自己可以单独使用。
- Callable不能创建线程,但是Thread可以。
说到底: Callable就是为了线程池准备的,而Thread就是为了独立运行使用。
2. CompletableFuture
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.ToString;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Random;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.TimeUnit;
/**
* 假设你能提供这样一种服务:
* 给你一个渠道列表, 里面包含各种电商的渠道, 你要从这些渠道里面获取某个商品的价格,然后找出最低的价格打印出来。
*/
public class CompletableFutureDemo {
//渠道列表
private static List<Channel> channelList = Collections.synchronizedList(new ArrayList<>());
static {
channelList.add(new Channel("淘宝",1.00));
channelList.add(new Channel("天猫",2.00));
channelList.add(new Channel("拼多多",3.00));
channelList.add(new Channel("美团",4.00));
}
/**
* 随机睡眠一段时间,模拟网络请求爬取数据
*/
private static void delay() throws InterruptedException {
int delayTime = new Random().nextInt(5000);
TimeUnit.MILLISECONDS.sleep(delayTime);
System.out.println("线程睡眠了"+delayTime+"毫秒");
}
public static void main(String[] args) {
long start = System.currentTimeMillis();
CompletableFuture<Double>[] completableFutures = new CompletableFuture[channelList.size()];
for (int i = 0; i < channelList.size(); i++) {
int j = i;
completableFutures[i] = CompletableFuture.supplyAsync(() -> {
try {
delay();
} catch (InterruptedException e) {
e.printStackTrace();
}
return channelList.get(j).getPrice();
});
}
CompletableFuture.allOf(completableFutures).join();
long end = System.currentTimeMillis();
System.out.println("耗时"+(end-start)+"毫秒");
}
/**
* 渠道类
*/
@Data
@AllArgsConstructor
@ToString
private static class Channel{
private String name; //渠道名字
private Double price; //商品在该渠道内的价格
}
}
3. ThreadPoolExecutor
3.1 ThreadPoolExecutor 继承结构
3.2 ThreadPoolExecutor 的7个构造参数
/**
* Creates a new {@code ThreadPoolExecutor} with the given initial
* parameters.
*
* @param corePoolSize the number of threads to keep in the pool, even
* if they are idle, unless {@code allowCoreThreadTimeOut} is set
* 核心线程数量:
* @param maximumPoolSize the maximum number of threads to allow in the
* pool
* 最大线程数量:
* @param keepAliveTime when the number of threads is greater than
* the core, this is the maximum time that excess idle threads
* will wait for new tasks before terminating.
* 超时时间:线程池内不是核心线程的线程运行完毕后的等待时间, 超出后自行销毁。
* @param unit the time unit for the {@code keepAliveTime} argument
* 超时时间单位:
* @param workQueue the queue to use for holding tasks before they are
* executed. This queue will hold only the {@code Runnable}
* tasks submitted by the {@code execute} method.
* 工作队列: 必须是阻塞队列
* @param threadFactory the factory to use when the executor
* creates a new thread
* 线程工厂:JDK自带默认Executors.defaultThreadFactory()
* @param handler the handler to use when execution is blocked
* because the thread bounds and queue capacities are reached
* 拒绝策略:JDK自带4个拒绝策略,默认为Abort抛异常策略
* @throws IllegalArgumentException if one of the following holds:<br>
* {@code corePoolSize < 0}<br>
* {@code keepAliveTime < 0}<br>
* {@code maximumPoolSize <= 0}<br>
* {@code maximumPoolSize < corePoolSize}
* @throws NullPointerException if {@code workQueue}
* or {@code threadFactory} or {@code handler} is null
*/
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory,
RejectedExecutionHandler handler)
3.3 ThreadPoolExecutor 模型
3.4 ThreadPoolExecutor 的4个特性
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;
public class ThreadPoolExecutorDemo {
/**
* 特性1: 如果运行的线程少于 corePoolSize,则 Executor 始终首选添加新的线程,而不进行排队
*/
private static void test1() throws InterruptedException {
//核心线程2个, 最大线程3个, 超时60秒,工作队列容量1,
ThreadPoolExecutor pool = new ThreadPoolExecutor(2,3,60L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(1));
pool.execute(()->run("任务1",0,TimeUnit.SECONDS)); //执行任务1
TimeUnit.SECONDS.sleep(2); //主线程睡眠2秒,保证线程1先执行完
pool.execute(()->run("任务2",0,TimeUnit.SECONDS)); //执行任务2
pool.shutdown(); //关闭线程池
System.out.println("特性1: 如果运行的线程少于 corePoolSize,则 Executor 始终首选添加新的线程,而不进行排队");
}
/**
* 特性2: 当池中正在运行的线程数大于等于corePoolSize时,新插入的任务进入workQueue排队(如果workQueue长度允许),等待空闲线程来执行。
*/
private static void test2() throws InterruptedException {
//核心线程2个, 最大线程3个, 超时60秒,工作队列容量1,
ThreadPoolExecutor pool = new ThreadPoolExecutor(2,3,60L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(1));
pool.execute(()->run("任务1",2,TimeUnit.SECONDS)); //执行任务1
pool.execute(()->run("任务2",2,TimeUnit.SECONDS)); //执行任务2
pool.execute(()->run("任务3",0,TimeUnit.SECONDS)); //执行任务3
pool.shutdown();//关闭线程池
//从实验结果上看,任务3会等待任务2执行完之后,有了空闲线程,才会执行。并没有新建线程执行任务3,这时maximumPoolSize=3这个参数不起作用。
System.out.println("特性2: 当池中正在运行的线程数大于等于corePoolSize时,新插入的任务进入workQueue排队(如果workQueue长度允许),等待空闲线程来执行。");
}
/**
* 特性3: 当队列里的任务数达到上限,并且池中正在运行的线程数小于maximumPoolSize,对于新加入的任务,新建线程。
*/
private static void test3() throws InterruptedException {
//核心线程2个, 最大线程3个, 超时60秒,工作队列容量2
ThreadPoolExecutor pool = new ThreadPoolExecutor(2,3,60L, TimeUnit.SECONDS,new ArrayBlockingQueue<>(2));
pool.execute(()->run("任务1",5,TimeUnit.SECONDS)); //执行任务1
pool.execute(()->run("任务2",5,TimeUnit.SECONDS)); //执行任务2
pool.execute(()->run("任务3",0,TimeUnit.SECONDS)); //执行任务3
pool.execute(()->run("任务4",0,TimeUnit.SECONDS)); //执行任务4
pool.execute(()->run("任务5",0,TimeUnit.SECONDS)); //执行任务5
pool.shutdown();//关闭线程池
//当任务4进入队列时发现队列的长度已经到了上限,所以无法进入队列排队,而此时正在运行的线程数(2)小于maximumPoolSize所以新建线程执行该任务。
//创建的新线程消费了队列里面所有任务
System.out.println("特性3: 当队列里的任务数达到上限,并且池中正在运行的线程数小于maximumPoolSize,对于新加入的任务,新建线程。");
}
/**
* 特性4:当队列里的任务数达到上限,并且池中正在运行的线程数等于maximumPoolSize,对于新加入的任务,执行拒绝策略(线程池默认的拒绝策略是抛异常)。
*/
private static void test4() throws InterruptedException {
//核心线程2个, 最大线程3个, 超时60秒,工作队列容量1, 调用者执行策略。
ThreadPoolExecutor pool = new ThreadPoolExecutor(2, 3, 60L, TimeUnit.SECONDS,
new ArrayBlockingQueue<>(1),
Executors.defaultThreadFactory(),
new ThreadPoolExecutor.CallerRunsPolicy()); //调用者执行策略,溢出的任务由调用者(这里是main)执行。
pool.execute(()->run("任务1",5,TimeUnit.SECONDS)); //执行任务1
pool.execute(()->run("任务2",5,TimeUnit.SECONDS)); //执行任务2
pool.execute(()->run("任务3",5,TimeUnit.SECONDS)); //执行任务3
pool.execute(()->run("任务4",5,TimeUnit.SECONDS)); //执行任务4
pool.execute(()->run("任务5",5,TimeUnit.SECONDS)); //执行任务5
pool.shutdown();
//当任务5加入时,队列达到上限,池内运行的线程数达到最大,故执行默认的拒绝策略,抛异常。
System.out.println("特性4:当队列里的任务数达到上限,并且池中正在运行的线程数等于maximumPoolSize,对于新加入的任务,执行拒绝策略(线程池默认的拒绝策略是抛异常)。");
}
/**
* 执行的任务
* @param taskName 任务名称
* @param sleepTime 睡眠时间
* @param timeUnit 时间单位
*/
private static void run(String taskName,long sleepTime,TimeUnit timeUnit){
try {
timeUnit.sleep(sleepTime);
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(taskName+",执行线程"+Thread.currentThread().getName());
}
public static void main(String[] args) throws InterruptedException {
// System.out.println("测试特性1");
// test1();
// System.out.println();
// System.out.println("测试特性2");
// test2();
// System.out.println("测试特性3");
// test3();
// System.out.println("测试特性4");
// test4();
}
}
结果:
测试特性1 线程pool-1-thread-1执行任务1 线程pool-1-thread-2执行任务2 特性1: 如果运行的线程少于 corePoolSize,则 Executor 始终首选添加新的线程,而不进行排队
测试特性2 特性2: 当池中正在运行的线程数大于等于corePoolSize时,新插入的任务进入workQueue排队(如果workQueue长度允许),等待空闲线程来执行。 线程pool-1-thread-2执行任务2 线程pool-1-thread-1执行任务1 线程pool-1-thread-2执行任务3
测试特性3 特性3: 当队列里的任务数达到上限,并且池中正在运行的线程数小于maximumPoolSize,对于新加入的任务,新建线程。 线程pool-1-thread-3执行任务5 线程pool-1-thread-3执行任务3 线程pool-1-thread-3执行任务4 线程pool-1-thread-1执行任务1 线程pool-1-thread-2执行任务2
测试特性4 线程pool-1-thread-2执行任务2 线程pool-1-thread-1执行任务1 线程pool-1-thread-3执行任务4 线程main执行任务5 特性4:当队列里的任务数达到上限,并且池中正在运行的线程数等于maximumPoolSize,对于新加入的任务,执行拒绝策略(线程池默认的拒绝策略是抛异常)。 线程pool-1-thread-2执行任务3
- 如果运行的线程少于 corePoolSize,则 Executor 始终首选添加新的线程,而不进行排队
- 当池中正在运行的线程数大于等于corePoolSize时,新插入的任务进入workQueue排队(如果workQueue长度允许),等待空闲线程来执行。
- 当队列里的任务数达到上限,并且池中正在运行的线程数小于maximumPoolSize,对于新加入的任务,新建线程。
- 当队列里的任务数达到上限,并且池中正在运行的线程数小于maximumPoolSize,对于新加入的任务,新建线程。
由此可见:任务的分配顺序是:核心线程->队列->最大线程->拒绝策略。
3.5 ThreadPoolExecutor 拒绝策略
JDK默认提供4种拒绝策略:
new ThreadPoolExecutor.AbortPolicy(); //抛异常
new ThreadPoolExecutor.CallerRunsPolicy(); //调用者处理任务
new ThreadPoolExecutor.DiscardPolicy(); //直接扔掉
new ThreadPoolExecutor.DiscardOldestPolicy(); //扔掉最老任务
自定义拒绝策略:
实现RejectedExecutionHandler接口
/**
* 自定义拒绝策略
*/
public class MyRejectedExecutionHandler implements RejectedExecutionHandler {
@Override
public void rejectedExecution(Runnable r, ThreadPoolExecutor executor) {
System.out.println("任务保存至kafka");
}
}
3.6 ThreadPoolExecutor 源码分析
1、常用变量的解释
// 1. `ctl`,可以看做一个int类型的数字,高3位表示线程池状态,低29位表示worker数量
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
// 2. `COUNT_BITS`,`Integer.SIZE`为32,所以`COUNT_BITS`为29
private static final int COUNT_BITS = Integer.SIZE - 3;
// 3. `CAPACITY`,线程池允许的最大线程数。1左移29位,然后减1,即为 2^29 - 1
private static final int CAPACITY = (1 << COUNT_BITS) - 1;
// runState is stored in the high-order bits
// 4. 线程池有5种状态,按大小排序如下:RUNNING < SHUTDOWN < STOP < TIDYING < TERMINATED
private static final int RUNNING = -1 << COUNT_BITS;
private static final int SHUTDOWN = 0 << COUNT_BITS;
private static final int STOP = 1 << COUNT_BITS;
private static final int TIDYING = 2 << COUNT_BITS;
private static final int TERMINATED = 3 << COUNT_BITS;
// Packing and unpacking ctl
// 5. `runStateOf()`,获取线程池状态,通过按位与操作,低29位将全部变成0
private static int runStateOf(int c) { return c & ~CAPACITY; }
// 6. `workerCountOf()`,获取线程池worker数量,通过按位与操作,高3位将全部变成0
private static int workerCountOf(int c) { return c & CAPACITY; }
// 7. `ctlOf()`,根据线程池状态和线程池worker数量,生成ctl值
private static int ctlOf(int rs, int wc) { return rs | wc; }
/*
* Bit field accessors that don't require unpacking ctl.
* These depend on the bit layout and on workerCount being never negative.
*/
// 8. `runStateLessThan()`,线程池状态小于xx
private static boolean runStateLessThan(int c, int s) {
return c < s;
}
// 9. `runStateAtLeast()`,线程池状态大于等于xx
private static boolean runStateAtLeast(int c, int s) {
return c >= s;
}
2、构造方法
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory,
RejectedExecutionHandler handler) {
// 基本类型参数校验
if (corePoolSize < 0 ||
maximumPoolSize <= 0 ||
maximumPoolSize < corePoolSize ||
keepAliveTime < 0)
throw new IllegalArgumentException();
// 空指针校验
if (workQueue == null || threadFactory == null || handler == null)
throw new NullPointerException();
this.corePoolSize = corePoolSize;
this.maximumPoolSize = maximumPoolSize;
this.workQueue = workQueue;
// 根据传入参数`unit`和`keepAliveTime`,将存活时间转换为纳秒存到变量`keepAliveTime `中
this.keepAliveTime = unit.toNanos(keepAliveTime);
this.threadFactory = threadFactory;
this.handler = handler;
}
3、提交执行task的过程
public void execute(Runnable command) {
if (command == null)
throw new NullPointerException();
/*
* Proceed in 3 steps:
*
* 1. If fewer than corePoolSize threads are running, try to
* start a new thread with the given command as its first
* task. The call to addWorker atomically checks runState and
* workerCount, and so prevents false alarms that would add
* threads when it shouldn't, by returning false.
*
* 2. If a task can be successfully queued, then we still need
* to double-check whether we should have added a thread
* (because existing ones died since last checking) or that
* the pool shut down since entry into this method. So we
* recheck state and if necessary roll back the enqueuing if
* stopped, or start a new thread if there are none.
*
* 3. If we cannot queue task, then we try to add a new
* thread. If it fails, we know we are shut down or saturated
* and so reject the task.
*/
int c = ctl.get();
// worker数量比核心线程数小,直接创建worker执行任务
if (workerCountOf(c) < corePoolSize) {
if (addWorker(command, true))
return;
c = ctl.get();
}
// worker数量超过核心线程数,任务直接进入队列
if (isRunning(c) && workQueue.offer(command)) {
int recheck = ctl.get();
// 线程池状态不是RUNNING状态,说明执行过shutdown命令,需要对新加入的任务执行reject()操作。
// 这儿为什么需要recheck,是因为任务入队列前后,线程池的状态可能会发生变化。
if (! isRunning(recheck) && remove(command))
reject(command);
// 这儿为什么需要判断0值,主要是在线程池构造方法中,核心线程数允许为0
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
// 如果线程池不是运行状态,或者任务进入队列失败,则尝试创建worker执行任务。
// 这儿有3点需要注意:
// 1. 线程池不是运行状态时,addWorker内部会判断线程池状态
// 2. addWorker第2个参数表示是否创建核心线程
// 3. addWorker返回false,则说明任务执行失败,需要执行reject操作
else if (!addWorker(command, false))
reject(command);
}
4、addworker方法源码解析
private boolean addWorker(Runnable firstTask, boolean core) {
retry:
// 外层自旋
for (;;) {
int c = ctl.get();
int rs = runStateOf(c);
// 这个条件写得比较难懂,我对其进行了调整,和下面的条件等价
// (rs > SHUTDOWN) ||
// (rs == SHUTDOWN && firstTask != null) ||
// (rs == SHUTDOWN && workQueue.isEmpty())
// 1. 线程池状态大于SHUTDOWN时,直接返回false
// 2. 线程池状态等于SHUTDOWN,且firstTask不为null,直接返回false
// 3. 线程池状态等于SHUTDOWN,且队列为空,直接返回false
// Check if queue empty only if necessary.
if (rs >= SHUTDOWN &&
! (rs == SHUTDOWN &&
firstTask == null &&
! workQueue.isEmpty()))
return false;
// 内层自旋
for (;;) {
int wc = workerCountOf(c);
// worker数量超过容量,直接返回false
if (wc >= CAPACITY ||
wc >= (core ? corePoolSize : maximumPoolSize))
return false;
// 使用CAS的方式增加worker数量。
// 若增加成功,则直接跳出外层循环进入到第二部分
if (compareAndIncrementWorkerCount(c))
break retry;
c = ctl.get(); // Re-read ctl
// 线程池状态发生变化,对外层循环进行自旋
if (runStateOf(c) != rs)
continue retry;
// 其他情况,直接内层循环进行自旋即可
// else CAS failed due to workerCount change; retry inner loop
}
}
boolean workerStarted = false;
boolean workerAdded = false;
Worker w = null;
try {
w = new Worker(firstTask);
final Thread t = w.thread;
if (t != null) {
final ReentrantLock mainLock = this.mainLock;
// worker的添加必须是串行的,因此需要加锁
mainLock.lock();
try {
// Recheck while holding lock.
// Back out on ThreadFactory failure or if
// shut down before lock acquired.
// 这儿需要重新检查线程池状态
int rs = runStateOf(ctl.get());
if (rs < SHUTDOWN ||
(rs == SHUTDOWN && firstTask == null)) {
// worker已经调用过了start()方法,则不再创建worker
if (t.isAlive()) // precheck that t is startable
throw new IllegalThreadStateException();
// worker创建并添加到workers成功
workers.add(w);
// 更新`largestPoolSize`变量
int s = workers.size();
if (s > largestPoolSize)
largestPoolSize = s;
workerAdded = true;
}
} finally {
mainLock.unlock();
}
// 启动worker线程
if (workerAdded) {
t.start();
workerStarted = true;
}
}
} finally {
// worker线程启动失败,说明线程池状态发生了变化(关闭操作被执行),需要进行shutdown相关操作
if (! workerStarted)
addWorkerFailed(w);
}
return workerStarted;
}
5、线程池worker任务单元
private final class Worker
extends AbstractQueuedSynchronizer
implements Runnable
{
/**
* This class will never be serialized, but we provide a
* serialVersionUID to suppress a javac warning.
*/
private static final long serialVersionUID = 6138294804551838833L;
/** Thread this worker is running in. Null if factory fails. */
final Thread thread;
/** Initial task to run. Possibly null. */
Runnable firstTask;
/** Per-thread task counter */
volatile long completedTasks;
/**
* Creates with given first task and thread from ThreadFactory.
* @param firstTask the first task (null if none)
*/
Worker(Runnable firstTask) {
setState(-1); // inhibit interrupts until runWorker
this.firstTask = firstTask;
// 这儿是Worker的关键所在,使用了线程工厂创建了一个线程。传入的参数为当前worker
this.thread = getThreadFactory().newThread(this);
}
/** Delegates main run loop to outer runWorker */
public void run() {
runWorker(this);
}
// 省略代码...
}
6、核心线程执行逻辑-runworker
final void runWorker(Worker w) {
Thread wt = Thread.currentThread();
Runnable task = w.firstTask;
w.firstTask = null;
// 调用unlock()是为了让外部可以中断
w.unlock(); // allow interrupts
// 这个变量用于判断是否进入过自旋(while循环)
boolean completedAbruptly = true;
try {
// 这儿是自旋
// 1. 如果firstTask不为null,则执行firstTask;
// 2. 如果firstTask为null,则调用getTask()从队列获取任务。
// 3. 阻塞队列的特性就是:当队列为空时,当前线程会被阻塞等待
while (task != null || (task = getTask()) != null) {
// 这儿对worker进行加锁,是为了达到下面的目的
// 1. 降低锁范围,提升性能
// 2. 保证每个worker执行的任务是串行的
w.lock();
// If pool is stopping, ensure thread is interrupted;
// if not, ensure thread is not interrupted. This
// requires a recheck in second case to deal with
// shutdownNow race while clearing interrupt
// 如果线程池正在停止,则对当前线程进行中断操作
if ((runStateAtLeast(ctl.get(), STOP) ||
(Thread.interrupted() &&
runStateAtLeast(ctl.get(), STOP))) &&
!wt.isInterrupted())
wt.interrupt();
// 执行任务,且在执行前后通过`beforeExecute()`和`afterExecute()`来扩展其功能。
// 这两个方法在当前类里面为空实现。
try {
beforeExecute(wt, task);
Throwable thrown = null;
try {
task.run();
} catch (RuntimeException x) {
thrown = x; throw x;
} catch (Error x) {
thrown = x; throw x;
} catch (Throwable x) {
thrown = x; throw new Error(x);
} finally {
afterExecute(task, thrown);
}
} finally {
// 帮助gc
task = null;
// 已完成任务数加一
w.completedTasks++;
w.unlock();
}
}
completedAbruptly = false;
} finally {
// 自旋操作被退出,说明线程池正在结束
processWorkerExit(w, completedAbruptly);
}
}
4. JDK自带的线程池
4.1 单例线程池
ExecutorService service = Executors.newSingleThreadExecutor();
单例线程池是一个只有1个线程的线程池,它只会用唯一的工作线程来执行任务,保证所有任务按照指定顺序执行。
4.2 缓存线程池
ExecutorService service = Executors.newCachedThreadPool();
缓存线程池是一个可缓存线程的线程池,如果线程池长度超过处理需求,可以灵活回收空闲线程,若无可回收则新建线程。
4.3 定长线程池
final int cpuCoreNum = 4;
ExecutorService service = Executors.newFixedThreadPool(cpuCoreNum);
定长线程池可以控制线程最大并发数,超过的线程会在队列中等待。
4.4 定时计划线程池
ScheduledExecutorService service = Executors.newScheduledThreadPool(4);
定时计划线程池支持定时及周期性任务执行。
5. ForkJoinPool
ForkJoinPool 适合于把一个大任务切分成很多很多的小任务来执行, 执行后汇总结果。
- 分解汇总的任务
- 用很少的线程可以执行很多的任务(子任务)TPE做不到先执行子任务
- 适用于CPU密集型场景
5.1 WorkStealingPool
WorkStealingPool
与 ThreadPoolExecutor
不同的地方在于WorkStealingPool
是每一个线程都维护了一个队列,如果一个线程执行完自己的队列的任务后,会从其他线程的尾部“偷”一个任务过来执行。所以这个线程池叫做WorkStealingPool
ExecutorService service = Executors.newWorkStealingPool();
6. 定义多少线程合适
- Ncpu: 是CPU的数量,可以通过
_Runtime.getRuntime().availableProcessors();_
获取 - Ucpu:是期望CPU的使用率,比如期望CPU满载则 Ucpu = 1。
- W/C:CPU的等待时间/执行时间(Wait/Computation)