线程池Executor实现原理
- 1、实现多线程的几种方式
- 1、继承Thread
- 2、实现Runnable
- 3、用线程池
- 2、run和start方法的区别
- 3、用多线程运行十万次需要多久的时间
- 1、自己创建多线程来执行
- 2、使用线程池来执行
- 4、创建Executor的三种方式与区别
- 区别
- 5、按照上述自定义的ThreadPoolExecutor，为什么当执行到第31次任务时会触发拒绝策略？
- 6、执行优先级
- 7、为什么线程池执行速度快
- 8、线程复用
- 总结
1、实现多线程的几种方式
1、继承Thread
public class ThreadDemo extends Thread {
private int i;
public ThreadDemo(int i){
this.i = i;
}
@Override
public void run() {
System.out.println(Thread.currentThread().getName() + "--" + i);
}
}2、实现Runnable
public class ThreadDemo implements Runnable {
private int i;
public ThreadDemo(int i){
this.i = i;
}
@Override
public void run() {
System.out.println(Thread.currentThread().getName() + "--" + i);
}
}3、用线程池
public class Test {
public static void main(String[] args) {
ExecutorService executorService1 = Executors.newFixedThreadPool(10);
ExecutorService executorService2 = Executors.newCachedThreadPool();
ExecutorService executorService3 = Executors.newSingleThreadExecutor();
for (int i = 0; i < 100; i++) {
executorService1.execute(new ThreadDemo(i));
}
executorService1.shutdown();
}
}2、run和start方法的区别
new ThreadDemo(0).run(); //方法级别的调用
new ThreadDemo(0).start(); //启动多线程3、用多线程运行十万次需要多久的时间
1、自己创建多线程来执行
public static void main(String[] args) throws InterruptedException {
long start = System.currentTimeMillis();
Random random = new Random();
List<Integer> list = new ArrayList<>();
for (int i = 0; i < 100000; i++) {
Thread thread = new Thread(()->{
list.add(random.nextInt());
});
thread.start();
thread.join();
}
System.out.println("时间：" + (System.currentTimeMillis() - start));
System.out.println("大小：" + list.size());
}时间：28037
大小：100000
2、使用线程池来执行
public static void main(String[] args) throws InterruptedException {
long start = System.currentTimeMillis();
Random random = new Random();
List<Integer> list = new ArrayList<>();
ExecutorService executorService = Executors.newSingleThreadExecutor();
for (int i = 0; i < 100000; i++) {
executorService.execute(new Thread(()->{
list.add(random.nextInt());
}));
}
executorService.shutdown();
executorService.awaitTermination(1, TimeUnit.DAYS);
System.out.println("时间：" + (System.currentTimeMillis() - start));
System.out.println("大小：" + list.size());
}时间：317
大小：100000
总结：使用线程池的效率会高很多
4、创建Executor的三种方式与区别
public class MyTask implements Runnable {
private int i;
public MyTask(int i) {
this.i = i;
}
@Override
public void run() {
System.out.println(Thread.currentThread().getName() + "---" + i);
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
public class Test {
public static void main(String[] args) {
ExecutorService executorService1 = Executors.newFixedThreadPool(10); //慢
ExecutorService executorService2 = Executors.newCachedThreadPool(); //快
ExecutorService executorService3 = Executors.newSingleThreadExecutor(); //最慢
for (int i = 0; i < 100; i++) {
executorService1.execute(new MyTask(i));
}
executorService1.shutdown();
}
}执行速度：executorService2 > executorService1 > executorService3
区别
ExecutorService executorService1 = Executors.newFixedThreadPool(10); //慢/**
* Creates a thread pool that reuses a fixed number of threads
* operating off a shared unbounded queue. At any point, at most
* {@code nThreads} threads will be active processing tasks.
* If additional tasks are submitted when all threads are active,
* they will wait in the queue until a thread is available.
* If any thread terminates due to a failure during execution
* prior to shutdown, a new one will take its place if needed to
* execute subsequent tasks. The threads in the pool will exist
* until it is explicitly {@link ExecutorService#shutdown shutdown}.
*
* @param nThreads the number of threads in the pool
* @return the newly created thread pool
* @throws IllegalArgumentException if {@code nThreads <= 0}
*/
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>());
}
/**
* Creates a {@code LinkedBlockingQueue} with a capacity of
* {@link Integer#MAX_VALUE}.
*/
public LinkedBlockingQueue() {
this(Integer.MAX_VALUE);
}ExecutorService executorService2 = Executors.newCachedThreadPool(); //快/**
* Creates a thread pool that creates new threads as needed, but
* will reuse previously constructed threads when they are
* available. These pools will typically improve the performance
* of programs that execute many short-lived asynchronous tasks.
* Calls to {@code execute} will reuse previously constructed
* threads if available. If no existing thread is available, a new
* thread will be created and added to the pool. Threads that have
* not been used for sixty seconds are terminated and removed from
* the cache. Thus, a pool that remains idle for long enough will
* not consume any resources. Note that pools with similar
* properties but different details (for example, timeout parameters)
* may be created using {@link ThreadPoolExecutor} constructors.
*
* @return the newly created thread pool
*/
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue<Runnable>());
}ExecutorService executorService3 = Executors.newSingleThreadExecutor(); //最慢/**
* Creates an Executor that uses a single worker thread operating
* off an unbounded queue. (Note however that if this single
* thread terminates due to a failure during execution prior to
* shutdown, a new one will take its place if needed to execute
* subsequent tasks.) Tasks are guaranteed to execute
* sequentially, and no more than one task will be active at any
* given time. Unlike the otherwise equivalent
* {@code newFixedThreadPool(1)} the returned executor is
* guaranteed not to be reconfigurable to use additional threads.
*
* @return the newly created single-threaded Executor
*/
public static ExecutorService newSingleThreadExecutor() {
return new FinalizableDelegatedExecutorService
(new ThreadPoolExecutor(1, 1,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>()));
}
/**
* Creates a {@code LinkedBlockingQueue} with a capacity of
* {@link Integer#MAX_VALUE}.
*/
public LinkedBlockingQueue() {
this(Integer.MAX_VALUE);
}/**
* Creates a new {@code ThreadPoolExecutor} with the given initial
* parameters and default thread factory and rejected execution handler.
* It may be more convenient to use one of the {@link Executors} factory
* methods instead of this general purpose constructor.
*
* @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.
* @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} is null
*/
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
Executors.defaultThreadFactory(), defaultHandler);
}
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory,
RejectedExecutionHandler handler)这三种方式的创建最终都是创建ThreadPoolExecutor对象，上面的三种方式都不推荐使用，第一种和第三种创建的的队列太大很容易造成OOM异常，第二种线程池太大，很容易造成CPU负载100%。
推荐使用自定义ThreadPoolExecutor，根据自己的需求灵活配置线程池
ExecutorService executorService = new ThreadPoolExecutor(10, 20, 10L, TimeUnit.MILLISECONDS, new ArrayBlockingQueue<Runnable>(10));5、按照上述自定义的ThreadPoolExecutor，为什么当执行到第31次任务时会触发拒绝策略？
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();
if (workerCountOf(c) < corePoolSize) {
if (addWorker(command, true))
return;
c = ctl.get();
}
if (isRunning(c) && workQueue.offer(command)) {
int recheck = ctl.get();
if (! isRunning(recheck) && remove(command))
reject(command);
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
else if (!addWorker(command, false))
reject(command);
}
这是因为提交任务的优先级是：
1、先判断核心线程数是否有空闲，如果有则由核心线程来执行；
2、如果核心线程满了，则放在任务队列里；
3、如果任务队列满了，则由非核心线程数来执行；
4、如果线程数达到最大时，则会触发拒绝策略
6、执行优先级
执行优先级：
1、先执行核心线程的任务
2、再执行非核心线程的任务
3、最后再执行队列里面的任务
7、为什么线程池执行速度快
private boolean addWorker(Runnable firstTask, boolean core) {
retry:
for (;;) {
int c = ctl.get();
int rs = runStateOf(c);
// Check if queue empty only if necessary.
if (rs >= SHUTDOWN &&
! (rs == SHUTDOWN &&
firstTask == null &&
! workQueue.isEmpty()))
return false;
for (;;) {
int wc = workerCountOf(c);
if (wc >= CAPACITY ||
wc >= (core ? corePoolSize : maximumPoolSize))
return false;
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 {
w = new Worker(firstTask); //创建任务
final Thread t = w.thread;
if (t != null) {
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
// Recheck while holding lock.
// Back out on ThreadFactory failure or if
// shut down before lock acquired.
int rs = runStateOf(ctl.get());
if (rs < SHUTDOWN ||
(rs == SHUTDOWN && firstTask == null)) {
if (t.isAlive()) // precheck that t is startable
throw new IllegalThreadStateException();
workers.add(w);
int s = workers.size();
if (s > largestPoolSize)
largestPoolSize = s;
workerAdded = true;
}
} finally {
mainLock.unlock();
}
if (workerAdded) {
t.start(); //启动任务线程
workerStarted = true;
}
}
} finally {
if (! workerStarted)
addWorkerFailed(w);
}
return workerStarted;
}Worker(Runnable firstTask) {
setState(-1); // inhibit interrupts until runWorker
this.firstTask = firstTask;
this.thread = getThreadFactory().newThread(this);
}
/** Delegates main run loop to outer runWorker */
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 {
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
if ((runStateAtLeast(ctl.get(), STOP) ||
(Thread.interrupted() &&
runStateAtLeast(ctl.get(), STOP))) &&
!wt.isInterrupted())
wt.interrupt();
try {
beforeExecute(wt, task);
Throwable thrown = null;
try {
task.run(); //最后是调用run方法来执行的
} 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);
}
}主要是因为线程池底层最终是来调用run方法来执行，而不是start方法，减少了线程的开销，大大提高了效率
8、线程复用
/**
* Performs cleanup and bookkeeping for a dying worker. Called
* only from worker threads. Unless completedAbruptly is set,
* assumes that workerCount has already been adjusted to account
* for exit. This method removes thread from worker set, and
* possibly terminates the pool or replaces the worker if either
* it exited due to user task exception or if fewer than
* corePoolSize workers are running or queue is non-empty but
* there are no workers.
*
* @param w the worker
* @param completedAbruptly if the worker died due to user exception
*/
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;
workers.remove(w);
} finally {
mainLock.unlock();
}
tryTerminate();
int c = ctl.get();
if (runStateLessThan(c, STOP)) { //当线程还在存活时间内，则继续使用线程来处理任务，这就是线程复用
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); //继续来处理任务
}
}总结
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