例如，我有一个生成某些类实例的库。每个实例必须有一个唯一的整数ID，因为这些实例表示发送到服务器的命令，并且每个命令必须有一个唯一的ID。由于允许多个线程并发发送命令，所以我使用AtomicInteger来生成这些id。另一种方法是使用某种锁和常规整数，但这既慢又不优雅。

我使用AtomicInteger来解决就餐哲学家的问题。

在我的解决方案中，使用AtomicInteger实例来表示fork，每个哲学家需要两个。每个哲学家都被标识为一个整数，从1到5。当一个哲学家使用一个fork时，AtomicInteger保存哲学家的值，从1到5，否则该fork没有被使用，因此AtomicInteger的值为-1。

AtomicInteger允许在一个原子操作中检查一个fork是否空闲，value==-1，如果空闲则将其设置为fork的所有者。参见下面的代码。

AtomicInteger fork0 = neededForks[0];//neededForks is an array that holds the forks needed per Philosopher
AtomicInteger fork1 = neededForks[1];
while(true){    
    if (Hungry) {
        //if fork is free (==-1) then grab it by denoting who took it
        if (!fork0.compareAndSet(-1, p) || !fork1.compareAndSet(-1, p)) {
          //at least one fork was not succesfully grabbed, release both and try again later
            fork0.compareAndSet(p, -1);
            fork1.compareAndSet(p, -1);
            try {
                synchronized (lock) {//sleep and get notified later when a philosopher puts down one fork                    
                    lock.wait();//try again later, goes back up the loop
                }
            } catch (InterruptedException e) {}

        } else {
            //sucessfully grabbed both forks
            transition(fork_l_free_and_fork_r_free);
        }
    }
}

因为compareAndSet方法不阻塞，它应该增加吞吐量，完成更多的工作。正如你所知道的，Dining Philosophers问题是在需要对资源进行受控访问时使用的，即需要fork，就像一个进程需要资源来继续工作一样。

例如，我有一个生成某些类实例的库。每个实例必须有一个唯一的整数ID，因为这些实例表示发送到服务器的命令，并且每个命令必须有一个唯一的ID。由于允许多个线程并发发送命令，所以我使用AtomicInteger来生成这些id。另一种方法是使用某种锁和常规整数，但这既慢又不优雅。

如果您查看AtomicInteger具有的方法，您将注意到它们倾向于对应于对int的常见操作。例如:

static AtomicInteger i;

// Later, in a thread
int current = i.incrementAndGet();

是线程安全的版本:

static int i;

// Later, in a thread
int current = ++i;

方法映射如下: ++i是i. incrementandget () i++就是i. getandincrement () ——i是i. decrementandget () i——是i. getanddecrement () I = x = I .set(x) X = I = X = I .get()

还有其他方便的方法，如compareAndSet或addAndGet

我能想到的最简单的例子是使递增成为一个原子操作。

使用标准int型:

private volatile int counter;

public int getNextUniqueIndex() {
    return counter++; // Not atomic, multiple threads could get the same result
}

AtomicInteger:

private AtomicInteger counter;

public int getNextUniqueIndex() {
    return counter.getAndIncrement();
}

后者是执行简单的突变效果(特别是计数或唯一索引)的一种非常简单的方法，而不必求助于同步所有访问。

More complex synchronization-free logic can be employed by using compareAndSet() as a type of optimistic locking - get the current value, compute result based on this, set this result iff value is still the input used to do the calculation, else start again - but the counting examples are very useful, and I'll often use AtomicIntegers for counting and VM-wide unique generators if there's any hint of multiple threads being involved, because they're so easy to work with I'd almost consider it premature optimisation to use plain ints.

While you can almost always achieve the same synchronization guarantees with ints and appropriate synchronized declarations, the beauty of AtomicInteger is that the thread-safety is built into the actual object itself, rather than you needing to worry about the possible interleavings, and monitors held, of every method that happens to access the int value. It's much harder to accidentally violate threadsafety when calling getAndIncrement() than when returning i++ and remembering (or not) to acquire the correct set of monitors beforehand.

AtomicInteger有两个主要用途:

As an atomic counter (incrementAndGet(), etc) that can be used by many threads concurrently As a primitive that supports compare-and-swap instruction (compareAndSet()) to implement non-blocking algorithms. Here is an example of non-blocking random number generator from Brian Göetz's Java Concurrency In Practice: public class AtomicPseudoRandom extends PseudoRandom { private AtomicInteger seed; AtomicPseudoRandom(int seed) { this.seed = new AtomicInteger(seed); } public int nextInt(int n) { while (true) { int s = seed.get(); int nextSeed = calculateNext(s); if (seed.compareAndSet(s, nextSeed)) { int remainder = s % n; return remainder > 0 ? remainder : remainder + n; } } } ... } As you can see, it basically works almost the same way as incrementAndGet(), but performs arbitrary calculation (calculateNext()) instead of increment (and processes the result before return).