本文主要介绍jdk中常用的同步控制工具以及并发容器, 其结构如下:
同步控制工具类
ReentrantLock
简而言之, 就是*度更高的synchronized, 主要具备以下优点.
- 可重入: 单线程可以重复进入，但要重复退出
- 可中断: lock.lockInterruptibly()
- 可限时: 超时不能获得锁，就返回false，不会永久等待构成死锁
- 公平锁: 先来先得, public ReentrantLock(boolean fair), 默认锁不公平的, 根据线程优先级竞争.
示例
public class ReenterLock implements Runnable {
public static ReentrantLock lock = new ReentrantLock();
public static int i = 0;
@Override
public void run() {
for (int j = 0; j < 10000; j++) {
lock.lock();
// 超时设置
// lock.tryLock(5, TimeUnit.SECONDS);
try {
i++;
} finally {
// 需要放在finally里释放, 如果上面lock了两次, 这边也要unlock两次
lock.unlock();
}
}
}
public static void main(String[] args) throws InterruptedException {
ReenterLock tl = new ReenterLock();
Thread t1 = new Thread(tl);
Thread t2 = new Thread(tl);
t1.start();
t2.start();
t1.join();
t2.join();
System.out.println(i);
}
}
中断死锁
线程1, 线程2分别去获取lock1, lock2, 触发死锁. 最终通过DeadlockChecker来触发线程中断.
public class DeadLock implements Runnable{
public static ReentrantLock lock1 = new ReentrantLock();
public static ReentrantLock lock2 = new ReentrantLock();
int lock;
public DeadLock(int lock) {
this.lock = lock;
}
@Override
public void run() {
try {
if (lock == 1){
lock1.lockInterruptibly();
try {
Thread.sleep(500);
}catch (InterruptedException e){}
lock2.lockInterruptibly();
}else {
lock2.lockInterruptibly();
try {
Thread.sleep(500);
}catch (InterruptedException e){}
lock1.lockInterruptibly();
}
}catch (InterruptedException e){
e.printStackTrace();
}finally {
if (lock1.isHeldByCurrentThread())
lock1.unlock();
if (lock2.isHeldByCurrentThread())
lock2.unlock();
System.out.println(Thread.currentThread().getId() + "线程中断");
}
}
public static void main(String[] args) throws InterruptedException {
DeadLock deadLock1 = new DeadLock(1);
DeadLock deadLock2 = new DeadLock(2);
// 线程1, 线程2分别去获取lock1, lock2. 导致死锁
Thread t1 = new Thread(deadLock1);
Thread t2 = new Thread(deadLock2);
t1.start();
t2.start();
Thread.sleep(1000);
// 死锁检查, 触发中断
DeadlockChecker.check();
}
}
public class DeadlockChecker {
private final static ThreadMXBean mbean = ManagementFactory.getThreadMXBean();
final static Runnable deadLockCheck = new Runnable() {
@Override
public void run() {
while (true) {
long[] deadlockedThreadlds = mbean.findDeadlockedThreads();
if (deadlockedThreadlds != null) {
ThreadInfo[] threadInfos = mbean.getThreadInfo(deadlockedThreadlds);
for (Thread t : Thread.getAllStackTraces().keySet()) {
for (int i = 0; i < threadInfos.length; i++) {
if (t.getId() == threadInfos[i].getThreadId()) {
t.interrupt();
try {
Thread.sleep(5000);
} catch (InterruptedException e) {
}
}
}
}
}
}
}
};
public static void check() {
Thread t = new Thread(deadLockCheck);
t.setDaemon(true);
t.start();
}
}
Condition
类似于 Object.wait()和Object.notify(), 需要与ReentrantLock结合使用.
具体API如下:
// await()方法会使当前线程等待，同时释放当前锁，当其他线程中使用signal()时或者signalAll()方法时，
// 线程会重新获得锁并继续执行。或者当线程被中断时，也能跳出等待。这和Object.wait()方法很相似。
void await() throws InterruptedException;
// awaitUninterruptibly()方法与await()方法基本相同，但是它并不会再等待过程中响应中断。
void awaitUninterruptibly();
long awaitNanos(long nanosTimeout) throws InterruptedException;
boolean await(long time, TimeUnit unit) throws InterruptedException;
boolean awaitUntil(Date deadline) throws InterruptedException;
// singal()方法用于唤醒一个在等待中的线程。相对的singalAll()方法会唤醒所有在等待中的线程。
// 这和Obejct.notify()方法很类似。
void signal();
void signalAll();
示例
public class ReenterLockCondition implements Runnable{
public static ReentrantLock lock = new ReentrantLock();
public static Condition condition = lock.newCondition();
@Override
public void run() {
try {
lock.lock();
condition.await();
System.out.println("Thread is going on");
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
// 注意放到finally中释放
lock.unlock();
}
}
public static void main(String[] args) throws InterruptedException {
ReenterLockCondition t1 = new ReenterLockCondition();
Thread tt = new Thread(t1);
tt.start();
Thread.sleep(2000);
System.out.println("after sleep, signal!");
// 通知线程tt继续执行. 唤醒同样需要重新获得锁
lock.lock();
condition.signal();
lock.unlock();
}
}
Semaphore信号量
锁一般都是互斥排他的, 而信号量可以认为是一个共享锁,
允许N个线程同时进入临界区, 但是超出许可范围的只能等待.
如果N = 1, 则类似于lock.
具体API如下, 通过acquire获取信号量, 通过release释放
public void acquire()
public void acquireUninterruptibly()
public boolean tryAcquire()
public boolean tryAcquire(long timeout, TimeUnit unit)
public void release()
示例
模拟20个线程, 但是信号量只设置了5个许可.
因此线程是按序每2秒5个的打印job done.
public class SemapDemo implements Runnable{
// 设置5个许可
final Semaphore semp = new Semaphore(5);
@Override
public void run() {
try {
semp.acquire();
// 模拟线程耗时操作
Thread.sleep(2000L);
System.out.println("Job done! " + Thread.currentThread().getId());
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
semp.release();
}
}
public static void main(String[] args){
ExecutorService service = Executors.newFixedThreadPool(20);
final SemapDemo demo = new SemapDemo();
for (int i = 0; i < 20; i++) {
service.submit(demo);
}
}
}
ReadWriteLock
读写分离锁, 可以大幅提升系统并行度.
- 读-读不互斥：读读之间不阻塞。
- 读-写互斥：读阻塞写，写也会阻塞读。
- 写-写互斥：写写阻塞。
示例
使用方法与ReentrantLock类似, 只是读写锁分离.
private static ReentrantReadWriteLock readWriteLock=new ReentrantReadWriteLock();
private static Lock readLock = readWriteLock.readLock();
private static Lock writeLock = readWriteLock.writeLock();
CountDownLatch倒数计时器
一种典型的场景就是火箭发射。在火箭发射前，为了保证万无一失，往往还要进行各项设备、仪器的检查。
只有等所有检查完毕后，引擎才能点火。这种场景就非常适合使用CountDownLatch。它可以使得点火线程,
等待所有检查线程全部完工后，再执行.
示例
public class CountDownLatchDemo implements Runnable{
static final CountDownLatch end = new CountDownLatch(10);
static final CountDownLatchDemo demo = new CountDownLatchDemo();
@Override
public void run() {
try {
Thread.sleep(new Random().nextInt(10) * 1000);
System.out.println("check complete!");
end.countDown();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
public static void main(String[] args) throws InterruptedException {
ExecutorService service = Executors.newFixedThreadPool(10);
for (int i = 0; i < 10; i++) {
service.submit(demo);
}
// 等待检查
end.await();
// 所有线程检查完毕, 发射火箭.
System.out.println("fire");
service.shutdown();
}
}
CyclicBarrier循环栅栏
Cyclic意为循环，也就是说这个计数器可以反复使用。比如，假设我们将计数器设置为10。那么凑齐
第一批10个线程后，计数器就会归零，然后接着凑齐下一批10个线程.
示例
public class CyclicBarrierDemo {
public static class Soldier implements Runnable {
private String soldier;
private final CyclicBarrier cyclic;
Soldier(CyclicBarrier cyclic, String soldier) {
this.cyclic = cyclic;
this.soldier = soldier;
}
@Override
public void run() {
try {
// 等待所有士兵到期
cyclic.await();
doWork();
// 等待所有士兵完成工作
cyclic.await();
} catch (InterruptedException e) {
e.printStackTrace();
} catch (BrokenBarrierException e) {
e.printStackTrace();
}
}
void doWork() {
try {
Thread.sleep(Math.abs(new Random().nextInt() % 10000));
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(soldier + " 任务完成!");
}
}
public static class BarrierRun implements Runnable {
boolean flag;
int N;
public BarrierRun(boolean flag, int n) {
this.flag = flag;
N = n;
}
@Override
public void run() {
if (flag) {
System.out.println("士兵:" + N + "个, 任务完成!");
} else {
System.out.println("士兵:" + N + "个, 集合完毕!");
flag = true;
}
}
}
public static void main(String[] args){
final int N = 5;
Thread[] allSoldier = new Thread[N];
boolean flag = false;
CyclicBarrier cyclic = new CyclicBarrier(N, new BarrierRun(flag, N));
// 设置屏障点, 主要为了执行这个方法.
System.out.println("集合任务!");
for (int i = 0; i < N; i++) {
System.out.println("士兵" + i + " 报到!");
allSoldier[i] = new Thread(new Soldier(cyclic, "士兵" + i));
allSoldier[i].start();
}
}
}
结果
集合任务!
士兵0 报到!
士兵1 报到!
士兵2 报到!
士兵3 报到!
士兵4 报到!
士兵:5个, 集合完毕!
士兵3 任务完成!
士兵1 任务完成!
士兵0 任务完成!
士兵4 任务完成!
士兵2 任务完成!
士兵:5个, 任务完成!
LockSupport
一个线程阻塞工具, 可以在任意位置让线程阻塞.
与suspend()比较, 如果unpark发生在park之前, 并不会导致线程冻结, 也不需要获取锁.
API
LockSupport.park();
LockSupport.unpark(t1);
中断响应
能够响应中断，但不抛出异常。
中断响应的结果是，park()函数的返回，可以从Thread.interrupted()得到中断标志
public class LockSupportDemo {
public static Object u = new Object();
static ChangeObjectThread t1 = new ChangeObjectThread("t1");
static ChangeObjectThread t2 = new ChangeObjectThread("t2");
public static class ChangeObjectThread extends Thread {
public ChangeObjectThread(String name) {
super(name);
}
@Override
public void run() {
synchronized (u) {
System.out.println("in " + getName());
LockSupport.park();
}
}
}
public static void main(String[] args) throws InterruptedException {
t1.start();
Thread.sleep(100);
t2.start();
LockSupport.unpark(t1);
LockSupport.unpark(t2);
t1.join();
t2.join();
}
}
并发容器
Collections.synchronizedMap
其本质是在读写map操作上都加了锁, 因此不推荐在高并发场景使用.
ConcurrentHashMap
内部使用分区Segment来表示不同的部分, 每个分区其实就是一个小的hashtable. 各自有自己的锁.
只要多个修改发生在不同的分区, 他们就可以并发的进行. 把一个整体分成了16个Segment, 最高支持16个线程并发修改.
代码中运用了很多volatile声明共享变量, 第一时间获取修改的内容, 性能较好.
public V put(K key, V value) {
ConcurrentHashMap.Segment<K,V> s;
if (value == null)
throw new NullPointerException();
int hash = hash(key);
int j = (hash >>> segmentShift) & segmentMask;
// 通过unsafe对j进行偏移来寻找key所对应的分区
if ((s = (ConcurrentHashMap.Segment<K,V>)UNSAFE.getObject // nonvolatile; recheck
(segments, (j << SSHIFT) + SBASE)) == null) // in ensureSegment
// 如果分区不存在, 则创建新的分区
s = ensureSegment(j);
// kv放到分区中
return s.put(key, hash, value, false);
}
Segment.put源码
Segment(float lf, int threshold, ConcurrentHashMap.HashEntry<K,V>[] tab) {
this.loadFactor = lf;
this.threshold = threshold;
this.table = tab;
}
final V put(K key, int hash, V value, boolean onlyIfAbsent) {
// tryLock通过无锁cas操作尝试获取锁(无等待), 继承自ReentrantLock.
// 如果成功则, node = null
// 如果不成功, 则可能其他线程已经在插入数据了,
// 此时会尝试继续获取锁tryLock, 自旋MAX_SCAN_RETRIES次, 若还是拿不到锁才开始lock
ConcurrentHashMap.HashEntry<K,V> node = tryLock() ? null :
scanAndLockForPut(key, hash, value);
V oldValue;
try {
ConcurrentHashMap.HashEntry<K,V>[] tab = table;
// 获取分区中哪一个entry链的index
int index = (tab.length - 1) & hash;
// 获取第一个entry
ConcurrentHashMap.HashEntry<K,V> first = entryAt(tab, index);
for (ConcurrentHashMap.HashEntry<K,V> e = first;;) {
// e != null , 存在hash冲突, 把他加到当前链表中
if (e != null) {
K k;
if ((k = e.key) == key ||
(e.hash == hash && key.equals(k))) {
oldValue = e.value;
if (!onlyIfAbsent) {
e.value = value;
++modCount;
}
break;
}
e = e.next;
}
else {
// 无hash冲突, new entry
if (node != null)
node.setNext(first);
else
node = new ConcurrentHashMap.HashEntry<K,V>(hash, key, value, first);
int c = count + 1;
// 空间大小超出阈值, 需要rehash, 翻倍空间.
if (c > threshold && tab.length < MAXIMUM_CAPACITY)
rehash(node);
else
//放到分区中
setEntryAt(tab, index, node);
++modCount;
count = c;
oldValue = null;
break;
}
}
} finally {
unlock();
}
return oldValue;
}
如果想要对ConcurrentHashMap排序, 则可以使用ConcurrentSkipListMap,
他支持并发排序, 是一个线程安全的类似TreeMap的实现.
BlockingQueue
阻塞队列, 主要用于多线程之间共享数据.
当一个线程读取数据时, 如果队列是空的, 则当前线程会进入等待状态.
如果队列满了, 当一个线程尝试写入数据时, 同样会进入等待状态.
适用于生产消费者模型.
其源码实现也相对简单.
public void put(E e) throws InterruptedException {
checkNotNull(e);
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
try {
// 队列满了, 写进入等待
while (count == items.length)
notFull.await();
insert(e);
} finally {
lock.unlock();
}
}
public E take() throws InterruptedException {
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
try {
// 队列空的, 读进入等待
while (count == 0)
notEmpty.await();
return extract();
} finally {
lock.unlock();
}
}
因为BlockingQueue在put take等操作有锁, 因此非高性能容器,
如果需要高并发支持的队列, 则可以使用ConcurrentLinkedQueue. 他内部也是运用了大量无锁操作.
CopyOnWriteArrayList
CopyOnWriteArrayList通过在新增元素时, 复制一份新的数组出来, 并在其中写入数据, 之后将原数组引用指向到新数组.
其Add操作是在内部通过ReentrantLock进行锁保护, 防止多线程场景复制多份数组.
而Read操作内部无锁, 直接返回数组引用, 并发下效率高, 因此适用于读多写少的场景.
源码
public boolean add(E e) {
final ReentrantLock lock = this.lock;
// 写数据的锁
lock.lock();
try {
Object[] elements = getArray();
int len = elements.length;
// 复制到新的数组
Object[] newElements = Arrays.copyOf(elements, len + 1);
// 加入新元素
newElements[len] = e;
// 修改引用
setArray(newElements);
return true;
} finally {
lock.unlock();
}
}
final void setArray(Object[] a) {
array = a;
}
// 读的时候无锁
public E get(int index) {
return get(getArray(), index);
}
示例
使用10个读线程, 100个写线程. 如果使用ArrayList实现, 那么有可能是在运行过程中抛出ConcurrentModificationException.
原因很简单, ArrayList在遍历的时候会check modCount是否发生变化, 如果一边读一边写就会抛异常.
public class CopyOnWriteListDemo {
static List<UUID> list = new CopyOnWriteArrayList<UUID>();
// static List<UUID> list = new ArrayList<UUID>();
// 往list中写数据
public static class AddThread implements Runnable {
@Override
public void run() {
UUID uuid = UUID.randomUUID();
list.add(uuid);
System.out.println("++Add uuid : " + uuid);
}
}
// 从list中读数据
public static class ReadThread implements Runnable {
@Override
public void run() {
System.out.println("start read size: " + list.size() + " thread : " + Thread.currentThread().getName());
for (UUID uuid : list) {
System.out.println("Read uuid : " + uuid + " size : " + list.size() + "thread: " + Thread.currentThread().getName());
}
}
}
public static void main(String[] args) throws InterruptedException {
initThread(new AddThread(), 10);
initThread(new ReadThread(), 100);
}
private static void initThread(Runnable runnable, int maxNum) throws InterruptedException {
Thread[] ts = new Thread[maxNum];
for (int k = 0; k < maxNum; k++) {
ts[k] = new Thread(runnable);
}
for (int k = 0; k < maxNum; k++) {
ts[k].start();
}
}
}
下图运行结果中可以看出来, 同一个线程, 即使在读的过程中发生了size变化, 也不会抛出ConcurrentModificationException