线程
线程是调度CPU的最小单元，也叫轻量级进程LWP(Light Weight Process)
无论使用何种编程语言编写多线程程序，最终都是通过调用操作系统的线程来执行任务。
内核线程(KLT): 由操作系统来负责多线程调度的多线程实现方式，叫做内核线程。
应用程序运行在用户空间，通过系统调用才能实现对内核线程的操作。而系统调用会导致用户态和内核态的上下文切换。
用户线程(ULT)：为了解决内核线程存在的弊端（内核态和用户态的上下文切换），用户线程只是一个外壳。应用程序操作用户线程（创建、使用、销毁等），都是在用户空间完成的，不需要操作系统内核的参与，这样就避免了系统调用带来的用户态和内核态的上下文切换。
Java内核线程模型：1:1模型：用户空间中的一个用户线程对应内核空间中的一个内核线程。
线程池： Java线程的创建和销毁是依赖于系统内核，通过JVM调用系统库执行。需要进行操作系统状态的切换。为避免资源过度消耗所以用线程池来重用创建的线程。并统一分配，调优和监控。
线程池
/**
* 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)
阻塞队列：线程安全，永远只有一个线程能够进行入队或者出队操作。
SynchronousQueue ：同步队列，放一个拿一个。 newCachedThreadPool 就是用的这个，可能会创建大量的线程。导致CPU干爆。
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue<Runnable>());
}
LinkedBlockingQueue：如果为指定容量，则为：Integer.MAX_VALUE。所以如果有大量请求，可能会出现内存溢出。
public static ExecutorService newFixedThreadPool(int nThreads, ThreadFactory threadFactory) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>(),
threadFactory);
}
状态
线程状态：
线程池状态：
当所有的任务已终止，ctl记录的任务数为0，线程池的状态会变为TIDYING状态；当线程池的状态变为TIDYING状态时，会调用钩子函数terminated(),该方法在ThreadPoolExecutor中是空的，若用户想在线程池变为TIDYING时进行相应的处理，就需要重载terminated()函数实现
ctl
/**
* The main pool control state, ctl, is an atomic integer packing
* two conceptual fields
* workerCount, indicating the effective number of threads
* runState, indicating whether running, shutting down etc
*
* In order to pack them into one int, we limit workerCount to
* (2^29)-1 (about 500 million) threads rather than (2^31)-1 (2
* billion) otherwise representable. If this is ever an issue in
* the future, the variable can be changed to be an AtomicLong,
* and the shift/mask constants below adjusted. But until the need
* arises, this code is a bit faster and simpler using an int.
*
* The workerCount is the number of workers that have been
* permitted to start and not permitted to stop. The value may be
* transiently different from the actual number of live threads,
* for example when a ThreadFactory fails to create a thread when
* asked, and when exiting threads are still performing
* bookkeeping before terminating. The user-visible pool size is
* reported as the current size of the workers set.
*
* The runState provides the main lifecycle control, taking on values:
*
* RUNNING: Accept new tasks and process queued tasks
* SHUTDOWN: Don't accept new tasks, but process queued tasks
* STOP: Don't accept new tasks, don't process queued tasks,
* and interrupt in-progress tasks
* TIDYING: All tasks have terminated, workerCount is zero,
* the thread transitioning to state TIDYING
* will run the terminated() hook method
* TERMINATED: terminated() has completed
*
* The numerical order among these values matters, to allow
* ordered comparisons. The runState monotonically increases over
* time, but need not hit each state. The transitions are:
*
* RUNNING -> SHUTDOWN
* On invocation of shutdown(), perhaps implicitly in finalize()
* (RUNNING or SHUTDOWN) -> STOP
* On invocation of shutdownNow()
* SHUTDOWN -> TIDYING
* When both queue and pool are empty
* STOP -> TIDYING
* When pool is empty
* TIDYING -> TERMINATED
* When the terminated() hook method has completed
*
* Threads waiting in awaitTermination() will return when the
* state reaches TERMINATED.
*
* Detecting the transition from SHUTDOWN to TIDYING is less
* straightforward than you'd like because the queue may become
* empty after non-empty and vice versa during SHUTDOWN state, but
* we can only terminate if, after seeing that it is empty, we see
* that workerCount is 0 (which sometimes entails a recheck -- see
* below).
*/
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
private static final int COUNT_BITS = Integer.SIZE - 3;
private static final int CAPACITY = (1 << COUNT_BITS) - 1;
// runState is stored in the high-order bits
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;
ctl ：Integer 32位
高3位记录线程池生命状态
低29位记录当前工作线程数
