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CountDownLatch
- CountDownLatchExample1
package com.alan.concurrency.example.aqs;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
@Slf4j
public class CountDownLatchExample1 {
private final static int threadCount = 200;
public static void main(String[] args) throws InterruptedException {
ExecutorService exec = Executors.newCachedThreadPool();
final CountDownLatch countDownLatch = new CountDownLatch(threadCount);
for (int i = 0; i < threadCount; i++) {
{
int threadNum = i;
exec.execute(() -> {
try {
test(threadNum);
} catch (InterruptedException e) {
log.error("InterruptedException", e);
} finally {
countDownLatch.countDown();
}
});
}
}
//通过countDown()和await()能保证所有线程执行完成后，再调用log.info("finish")
countDownLatch.await();
log.info("finish");
exec.shutdown();
}
public static void test(int threadNum) throws InterruptedException {
Thread.sleep(100);
log.info("{}",threadNum);
}
}
- CountDownLatchExample2 限制指定时间完成
package com.alan.concurrency.example.aqs;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
@Slf4j
public class CountDownLatchExample2 {
private final static int threadCount = 200;
public static void main(String[] args) throws InterruptedException {
ExecutorService exec = Executors.newCachedThreadPool();
final CountDownLatch countDownLatch = new CountDownLatch(threadCount);
for (int i = 0; i < threadCount; i++) {
{
int threadNum = i;
exec.execute(() -> {
try {
test(threadNum);
} catch (InterruptedException e) {
log.error("InterruptedException", e);
} finally {
countDownLatch.countDown();
}
});
}
}
//通过countDown()和await()能保证所有线程执行完成后，再调用log.info("finish")
//设置超时时间10毫秒
countDownLatch.await(10,TimeUnit.MILLISECONDS);
log.info("finish");
//是先让当前线程任务都执行完成后，才进行shutdown操作
exec.shutdown();
}
public static void test(int threadNum) throws InterruptedException {
Thread.sleep(100);
log.info("{}",threadNum);
}
}
Semaphore 同步组件-信号量
Semaphore是一种在多线程环境下使用的设施，该设施负责协调各个线程，以保证它们能够正确、合理的使用公共资源的设施，也是操作系统中用于控制进程同步互斥的量。
以一个停车场是运作为例。为了简单起见，假设停车场只有三个车位，一开始三个车位都是空的。这时如果同时来了五辆车，看门人允许其中三辆不受阻碍的进入，然后放下车拦，剩下的车则必须在入口等待，此后来的车也都不得不在入口处等待。这时，有一辆车离开停车场，看门人得知后，打开车拦，放入一辆，如果又离开两辆，则又可以放入两辆，如此往复。
在这个停车场系统中，车位是公共资源，每辆车好比一个线程，看门人起的就是信号量的作用。
更进一步，信号量的特性如下：信号量是一个非负整数（车位数），所有通过它的线程（车辆）都会将该整数减一（通过它当然是为了使用资源），当该整数值为零时，所有试图通过它的线程都将处于等待状态。在信号量上我们定义两种操作： Wait（等待） 和 Release（释放）。 当一个线程调用Wait（等待）操作时，它要么通过然后将信号量减一，要么一直等下去，直到信号量大于一或超时。Release（释放）实际上是在信号量上执行加操作，对应于车辆离开停车场，该操作之所以叫做“释放”是因为加操作实际上是释放了由信号量守护的资源。
应用场景：只能访问有限的资源
1、设置数据库的连接数
2、设置数为1，将相当于单线程运行了。单一许可
package com.alan.concurrency.example.aqs;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
@Slf4j
public class SemaphoreExample1 {
private final static int threadCount = 200;
//设置允许的并发数为20
private final static Semaphore semaphore = new Semaphore(20);
public static void main(String[] args) throws InterruptedException {
ExecutorService exec = Executors.newCachedThreadPool();
for (int i = 0; i < threadCount; i++) {
{
int threadNum = i;
exec.execute(() -> {
try {
semaphore.acquire(); //获取一个许可
test(threadNum);
semaphore.release(); //释放一个许可
} catch (InterruptedException e) {
log.error("InterruptedException", e);
}
});
}
}
exec.shutdown();
}
public static void test(int threadNum) throws InterruptedException {
log.info("{}",threadNum);
Thread.sleep(1000);
}
}
- 多个许可
package com.alan.concurrency.example.aqs;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
@Slf4j
public class SemaphoreExample1 {
private final static int threadCount = 200;
//设置允许的并发数为20
private final static Semaphore semaphore = new Semaphore(20);
public static void main(String[] args) throws InterruptedException {
ExecutorService exec = Executors.newCachedThreadPool();
for (int i = 0; i < threadCount; i++) {
{
int threadNum = i;
exec.execute(() -> {
try {
semaphore.acquire(20);
test(threadNum);
semaphore.release(20);
} catch (InterruptedException e) {
log.error("InterruptedException", e);
}
});
}
}
exec.shutdown();
}
public static void test(int threadNum) throws InterruptedException {
log.info("{}",threadNum);
Thread.sleep(1000);
}
}
CyclicBarrier
- CyclicBarrier是一个同步工具类，它允许一组线程互相等待，直到到达某个公共屏障点。与CountDownLatch不同的是该barrier在释放等待线程后可以重用，所以称它为循环（Cyclic）的屏障（Barrier）。
- CyclicBarrier支持一个可选的Runnable命令，在一组线程中的最后一个线程到达之后（但在释放所有线程之前），该命令只在每个屏障点运行一次。若在继续所有参与线程之前更新共享状态，此屏障操作很有用。
package com.alan.concurrency.example.aqs;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CyclicBarrier;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
@Slf4j
public class CyclicBarrierExample1 {
private static CyclicBarrier barrier = new CyclicBarrier(5);
public static void main(String[] args) throws Exception {
ExecutorService executor= Executors.newCachedThreadPool();
for (int i = 0; i < 10; i++) {
final int threadNum = i;
Thread.sleep(1000);
executor.execute(()->{
try {
race(threadNum);
} catch (Exception e) {
e.printStackTrace();
}
});
}
}
private static void race(int threadNum) throws Exception{
Thread.sleep(1000);
log.info("{} is ready",threadNum);
barrier.await();
log.info("{} continue",threadNum);
}
}
ReentrantLock 与锁
可重入性：
从名字上理解，ReenTrantLock的字面意思就是再进入的锁，其实synchronized关键字所使用的锁也是可重入的，两者关于这个的区别不大。两者都是同一个线程没进入一次，锁的计数器都自增1，所以要等到锁的计数器下降为0时才能释放锁。锁的实现：
Synchronized是依赖于JVM实现的，而ReenTrantLock是JDK实现的，有什么区别，说白了就类似于操作系统来控制实现和用户自己敲代码实现的区别。前者的实现是比较难见到的，后者有直接的源码可供阅读。性能的区别：
在Synchronized优化以前，synchronized的性能是比ReenTrantLock差很多的，但是自从Synchronized引入了偏向锁，轻量级锁（自旋锁）后，两者的性能就差不多了，在两种方法都可用的情况下，官方甚至建议使用synchronized，其实synchronized的优化我感觉就借鉴了ReenTrantLock中的CAS技术。都是试图在用户态就把加锁问题解决，避免进入内核态的线程阻塞。功能区别：
便利性：很明显Synchronized的使用比较方便简洁，并且由编译器去保证锁的加锁和释放，而ReenTrantLock需要手工声明来加锁和释放锁，为了避免忘记手工释放锁造成死锁，所以最好在finally中声明释放锁。
锁的细粒度和灵活度：很明显ReenTrantLock优于Synchronized
- ReenTrantLock独有的能力：
1、ReenTrantLock可以指定是公平锁还是非公平锁。而synchronized只能是非公平锁。所谓的公平锁就是先等待的线程先获得锁。
2、ReenTrantLock提供了一个Condition（条件）类，用来实现分组唤醒需要唤醒的线程们，而不是像synchronized要么随机唤醒一个线程要么唤醒全部线程。
3、ReenTrantLock提供了一种能够中断等待锁的线程的机制，通过lock.lockInterruptibly()来实现这个机制。
package com.alan.concurrency.example.lock;
import com.alan.concurrency.annoations.ThreadSafe;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Slf4j
@ThreadSafe
public class LockExample2 {
//请求数1000
public static int clientTotal = 5000;
//同时并发执行的线程数
public static int threadTotal = 200;
public static int count = 0;
//通过Lock接口实现
private static Lock lock = new ReentrantLock();
private static void add(){
lock.lock();
try {
count++;
} finally {
lock.unlock();
}
}
public static void main(String[] args) throws InterruptedException {
//定义线程池ExecutorService接口
ExecutorService executorService = Executors.newCachedThreadPool();
//定义信号量,传入并发线程数 final修饰不允许重新赋值
final Semaphore semaphore = new Semaphore(threadTotal);
//定义计数器闭锁。传入请求总数
final CountDownLatch countDownLatch = new CountDownLatch(clientTotal);
for (int i = 0; i < clientTotal; i++) {
//通过匿名内部类方式
executorService.execute(new Runnable() {
@Override
public void run() {
try {
//semaphore控制并发数量
semaphore.acquire();
add();
semaphore.release();
} catch (InterruptedException e) {
log.error("exception",e);
}
//每次执行计数器减掉一个
countDownLatch.countDown();
}
});
}
countDownLatch.await();
executorService.shutdown();
log.info("count:{}",count);
}
}
- ReentrantReadWriteLock
package com.alan.concurrency.example.lock;
import com.alan.concurrency.annoations.ThreadSafe;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import java.util.Date;
import java.util.Map;
import java.util.Set;
import java.util.TreeMap;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
import java.util.concurrent.locks.ReentrantReadWriteLock;
@Slf4j
public class LockExample3 {
private final Map map = new TreeMap<>();
private final ReentrantReadWriteLock lock = new ReentrantReadWriteLock();
//分别定义读锁和写锁
private final Lock readLock = lock.readLock();
private final Lock writeLock = lock.writeLock();
public Data get(String key) {
readLock.lock();
try {
return map.get(key);
} finally {
readLock.unlock();
}
}
public Set getAllKeys(){
readLock.lock();
try {
return map.keySet();
} finally {
readLock.unlock();
}
}
public Data put(String key, Data value){
writeLock.lock();
try {
return map.put(key,value);
} finally {
writeLock.unlock();
}
}
}
- StampedLock
package com.alan.concurrency.example.lock;
import java.util.concurrent.locks.StampedLock;
public class LockExample4 {
class Point {
private double x, y;
private final StampedLock sl = new StampedLock();
void move(double deltaX, double deltaY) { // an exclusively locked method
long stamp = sl.writeLock();
try {
x += deltaX;
y += deltaY;
} finally {
sl.unlockWrite(stamp);
}
}
//下面看看乐观读锁案例
double distanceFromOrigin() { // A read-only method
long stamp = sl.tryOptimisticRead(); //获得一个乐观读锁
double currentX = x, currentY = y; //将两个字段读入本地局部变量
if (!sl.validate(stamp)) { //检查发出乐观读锁后同时是否有其他写锁发生？
stamp = sl.readLock(); //如果没有，我们再次获得一个读悲观锁
try {
currentX = x; // 将两个字段读入本地局部变量
currentY = y; // 将两个字段读入本地局部变量
} finally {
sl.unlockRead(stamp);
}
}
return Math.sqrt(currentX * currentX + currentY * currentY);
}
//下面是悲观读锁案例
void moveIfAtOrigin(double newX, double newY) { // upgrade
// Could instead start with optimistic, not read mode
long stamp = sl.readLock();
try {
while (x == 0.0 && y == 0.0) { //循环，检查当前状态是否符合
long ws = sl.tryConvertToWriteLock(stamp); //将读锁转为写锁
if (ws != 0L) { //这是确认转为写锁是否成功
stamp = ws; //如果成功 替换票据
x = newX; //进行状态改变
y = newY; //进行状态改变
break;
} else { //如果不能成功转换为写锁
sl.unlockRead(stamp); //我们显式释放读锁
stamp = sl.writeLock(); //显式直接进行写锁 然后再通过循环再试
}
}
} finally {
sl.unlock(stamp); //释放读锁或写锁
}
}
}
}
package com.alan.concurrency.example.lock;
import com.alan.concurrency.annoations.ThreadSafe;
import lombok.extern.slf4j.Slf4j;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Semaphore;
import java.util.concurrent.locks.StampedLock;
@Slf4j
@ThreadSafe
public class LockExample5 {
// 请求总数
public static int clientTotal = 5000;
// 同时并发执行的线程数
public static int threadTotal = 200;
public static int count = 0;
private final static StampedLock lock = new StampedLock();
public static void main(String[] args) throws Exception {
ExecutorService executorService = Executors.newCachedThreadPool();
final Semaphore semaphore = new Semaphore(threadTotal);
final CountDownLatch countDownLatch = new CountDownLatch(clientTotal);
for (int i = 0; i < clientTotal ; i++) {
executorService.execute(() -> {
try {
semaphore.acquire();
add();
semaphore.release();
} catch (Exception e) {
log.error("exception", e);
}
countDownLatch.countDown();
});
}
countDownLatch.await();
executorService.shutdown();
log.info("count:{}", count);
}
private static void add() {
long stamp = lock.writeLock();
try {
count++;
} finally {
lock.unlock(stamp);
}
}
}