发现漏写了一些java相关源码博客，导致很久以前看过，有一点印象，但是讲流程就完全记不得，这次复习下，还是偏个人整理向。
参数说明
/**
* 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
* @param maximumPoolSize the maximum number of threads to allow in the
* pool
* @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.
* @param unit the time unit for the {@code keepAliveTime} argument
* @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.
* @param threadFactory the factory to use when the executor
* creates a new thread
* @param handler the handler to use when execution is blocked
* because the thread bounds and queue capacities are reached
* @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) {
- corePoolSize：核心线程数，是要保留在线程池中的线程数
- maximumPoolSize：最大线程数，最多有多少个线程允许在池中
- keepAliveTime：当线程数量大于核心线程数，这个时间就是多出来的部分等待任务的最长时间，超过这个时间就嘎了
- unit：单位，服务上面个参数
- workQueue：保留被执行前的线程
- threadFactory：现成工厂
- handler：拒绝策略
Demo
public static void test(){
ExecutorService executor=new ThreadPoolExecutor(5, 10,
10L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>(10));
for (int i = 0; i < 1000000; i++) {
executor.submit(()->{
System.out.println(1111);
});
}
}
分析
提交
代码
public Future<?> submit(Runnable task) {
if (task == null) throw new NullPointerException();
//统一适配成RunnableFuture
RunnableFuture<Void> ftask = newTaskFor(task, null);
execute(ftask);
return ftask;
}
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.
1. 如果正在运行的线程少于 corePoolSize，请尝试使用给定的命令作为第一个任务启动一个新线程。对 addWorker 的调用以原子方式检查 runState 和 workerCount，因此通过返回 false 来防止错误警报，这些错误警报会在不应添加线程时添加线程。
*
* 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.
* 2.如果任务可以成功添加进队列，那么我们还需要仔细检查是否应该添加线程
（因为现有的自上次检查后死亡）或池自进入此方法后关闭。因此，我们重新检查状态，如果有必要，如果停止，则回滚排队，或者如果没有，则启动一个新线程。
* 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.
* 3. 如果我们不能排队任务，那么我们尝试添加一个新线程。如果它失败了，我们知道我们已经关闭或饱和，因此拒绝该任务。
*/
int c = ctl.get();
//小于核心线程数
if (workerCountOf(c) < corePoolSize) {
//添加worker，true：添加核心线程
if (addWorker(command, true))
return;
c = ctl.get();
}
//线程池处于运行状态，往阻塞队列扔任务
if (isRunning(c) && workQueue.offer(command)) {
int recheck = ctl.get();
//线程池关闭，则移除刚刚添加的任务，走reject策略
if (! isRunning(recheck) && remove(command))
reject(command);
//当一个worker都没有，添加worker
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
//无法往队列塞了，创建非核心线程
else if (!addWorker(command, false))
//新添加的队列塞不下了，最大线程数也创建满worker了，就执行拒绝策略
reject(command);
}
大致流程
- 如果当前Worker(工作线程数后面用Worker代替)数量少于核心线程数，则创建Worker并返回
- 如果当前Worker已经等于核心线程数，则尝试往阻塞队列塞
- 再次检查线程池状态，如果异常执行拒绝策略
- 如果没有Worker，添加非核心线程
- 如果当前Worker已经等于核心线程数，阻塞队列也无法塞了，尝试创建非核心Worker
- 如果阻塞队列也无法塞了，Worker也到了最大线程数了，就执行拒绝策略
添加Worker
代码
private boolean addWorker(Runnable firstTask, boolean core) {
retry:
for (;;) {
int c = ctl.get();
//高位表示运行状态
int rs = runStateOf(c);
// Check if queue empty only if necessary.
//线城池关闭状态
if (rs >= SHUTDOWN &&
! (rs == SHUTDOWN &&
firstTask == null &&
! workQueue.isEmpty()))
return false;
for (;;) {
//worker数量
int wc = workerCountOf(c);
if (wc >= CAPACITY ||
wc >= (core ? corePoolSize : maximumPoolSize))
return false;
//cas增加worker数量
if (compareAndIncrementWorkerCount(c))
break retry;
c = ctl.get(); // Re-read ctl
if (runStateOf(c) != rs)
continue retry;
// else CAS failed due to workerCount change; retry inner loop
}
}
boolean workerStarted = false;
boolean workerAdded = false;
Worker w = null;
try {
//封装成Woker
w = new Worker(firstTask);
//外部线程工厂创建再封装Worker，主义，t就是worker经过线程工厂封装后的
final Thread t = w.thread;
if (t != null) {
//加锁保证现成安全
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
// Recheck while holding lock.
// Back out on ThreadFactory failure or if
// shut down before lock acquired.
//再次减价线程池状态
int rs = runStateOf(ctl.get());
if (rs < SHUTDOWN ||
(rs == SHUTDOWN && firstTask == null)) {
if (t.isAlive()) // precheck that t is startable
throw new IllegalThreadStateException();
//添加进wokers（集合）
workers.add(w);
int s = workers.size();
if (s > largestPoolSize)
largestPoolSize = s;
workerAdded = true;
}
} finally {
mainLock.unlock();
}
//启动Worker
if (workerAdded) {
t.start();
workerStarted = true;
}
}
} finally {
if (! workerStarted)
addWorkerFailed(w);
}
return workerStarted;
}
大致流程
- 增加worker计数
- 添加worker进集合并启动
Worker内部
/**
* Class Worker mainly maintains interrupt control state for
* threads running tasks, along with other minor bookkeeping.
* This class opportunistically extends AbstractQueuedSynchronizer
* to simplify acquiring and releasing a lock surrounding each
* task execution. This protects against interrupts that are
* intended to wake up a worker thread waiting for a task from
* instead interrupting a task being run. We implement a simple
* non-reentrant mutual exclusion lock rather than use
* ReentrantLock because we do not want worker tasks to be able to
* reacquire the lock when they invoke pool control methods like
* setCorePoolSize. Additionally, to suppress interrupts until
* the thread actually starts running tasks, we initialize lock
* state to a negative value, and clear it upon start (in
* runWorker).
简单的说做了锁优化，更好并发及状态的控制，太多了，就不贴了
*/
private final class Worker
extends AbstractQueuedSynchronizer
implements Runnable
{
/**
* 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
//这个就是外部传入的线程
this.firstTask = firstTask;
this.thread = getThreadFactory().newThread(this);
}
public void run() {
runWorker(this);
}
final void runWorker(Worker w) {
Thread wt = Thread.currentThread();
Runnable task = w.firstTask;
w.firstTask = null;
w.unlock(); // allow interrupts
boolean completedAbruptly = true;
try {
//第一次就是外部传进来的，后面都是getTask获取
while (task != null || (task = getTask()) != null) {
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
//线程池停止，当前线程终端
if ((runStateAtLeast(ctl.get(), STOP) ||
(Thread.interrupted() &&
runStateAtLeast(ctl.get(), STOP))) &&
!wt.isInterrupted())
wt.interrupt();
try {
//do nothing
beforeExecute(wt, task);
Throwable thrown = null;
try {
//外部传入的任务执行
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 {
task = null;
w.completedTasks++;
w.unlock();
}
}
completedAbruptly = false;
} finally {
processWorkerExit(w, completedAbruptly);
}
}
private Runnable getTask() {
boolean timedOut = false; // Did the last poll() time out?
for (;;) {
int c = ctl.get();
//线程池状态
int rs = runStateOf(c);
// Check if queue empty only if necessary.
//下面有图片，大于SHUTDOWN都是异常状态，开始走关闭流程
if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
decrementWorkerCount();
return null;
}
//worker数量
int wc = workerCountOf(c);
// Are workers subject to culling?
// 线程数大于核心线程数
boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;
// timedOut：如果从队列中没有获取到
if ((wc > maximumPoolSize || (timed && timedOut))
&& (wc > 1 || workQueue.isEmpty())) {
//减少队列数量
if (compareAndDecrementWorkerCount(c))
return null;
continue;
}
//阻塞队列获取任务并返回
try {
Runnable r = timed ?
workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
workQueue.take();
if (r != null)
return r;
timedOut = true;
} catch (InterruptedException retry) {
timedOut = false;
}
}
}
//正常情况下只有减少非核心线程数的情况下才会进到
private void processWorkerExit(Worker w, boolean completedAbruptly) {
if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
decrementWorkerCount();
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
completedTaskCount += w.completedTasks;
//移除Worker
workers.remove(w);
} finally {
mainLock.unlock();
}
tryTerminate();
int c = ctl.get();
if (runStateLessThan(c, STOP)) {
if (!completedAbruptly) {
int min = allowCoreThreadTimeOut ? 0 : corePoolSize;
if (min == 0 && ! workQueue.isEmpty())
min = 1;
if (workerCountOf(c) >= min)
return; // replacement not needed
}
addWorker(null, false);
}
}
}
大致流程
- worker线程启动的时候，第一次正常执行
- 后续通过阻塞队列解耦
- 也是在这里判断是否要减少至核心线程数
总结
- 如果当前Worker(工作线程数后面用Worker代替)数量少于核心线程数，则创建Worker并执行
- 如果当前Worker已经等于核心线程数，则尝试往阻塞队列塞
- 再次检查线程池状态，如果异常执行拒绝策略
- 如果没有Worker，添加非核心线程
- 如果当前Worker已经等于核心线程数，阻塞队列也无法塞了，尝试创建非核心Worker并执行
- 如果阻塞队列也无法塞了，Worker也到了最大线程数（maximumPoolSize）了，就执行拒绝策略
- worker第一次用用户传进来的任务执行，后续通过阻塞队列解耦
- 通过阻塞队列超时判断是否要减少worker
