Day 2: Java内存模型与可见性

课程概述

Day 2 深入探索 Java 内存模型 (JMM)，理解多线程环境下数据不一致的根源，掌握 volatile 关键字的原理与应用，并通过实战代码理解可见性、原子性和有序性问题。

学习目标

• 深入理解 Java 内存模型的抽象结构
• 掌握 JMM 三大特性：原子性、可见性、有序性
• 熟练掌握 volatile 关键字的原理和使用场景
• 理解 happens-before 原则和内存屏障机制
• 掌握指令重排序问题和解决方案
• 完成可见性问题的实战练习

理论基础

1. Java 内存模型 (JMM) 概述

1.1 JMM 的抽象概念

Java 内存模型 (Java Memory Model, JMM) 是一个抽象的概念，它描述了 Java 程序中各种变量（线程共享变量）的访问规则，以及在 JVM 中将变量存储到内存和从内存中读取变量这样的底层细节。

1.2 JMM 的三大特性

1.3 内存间的交互操作

JMM 定义了 8 种原子操作来完成主内存和工作内存的交互：

2. happens-before 原则

2.1 什么是 happens-before

happens-before 是 JMM 中最重要的原则之一，它定义了两个操作之间的偏序关系。如果操作 A happens-before 操作 B，那么 A 操作的结果对 B 操作是可见的。

2.2 八大 happens-before 规则

1. 程序次序规则：在一个线程内，书写在前面的代码 happens-before 书写在后面的代码
2. 管程锁定规则：一个 unlock 操作 happens-before 后面对同一个锁的 lock 操作
3. volatile 变量规则：对一个 volatile 变量的写操作 happens-before 后面对这个变量的读操作
4. 线程启动规则：Thread 对象的 start() 方法 happens-before 于此线程的每一个动作
5. 线程终止规则：线程中的所有操作都 happens-before 对此线程的终止检测
6. 线程中断规则：对线程 interrupt() 方法的调用 happens-before 发生于被中断线程的代码检测到中断事件
7. 对象终结规则：一个对象的初始化完成 happens-before 于它的 finalize() 方法的开始
8. 传递性：如果 A happens-before B，且 B happens-before C，那么 A happens-before C

public class HappensBeforeDemo {
    private int value = 0;
    private volatile boolean flag = false;
    private final Object lock = new Object();

    // 示例1：程序次序规则
    public void programOrderRule() {
        int a = 1;        // 1
        int b = 2;        // 2 - 1 happens-before 2
        int c = a + b;    // 3 - 2 happens-before 3
        System.out.println(c); // 4 - 3 happens-before 4
    }

    // 示例2：管程锁定规则
    public void monitorLockRule() {
        synchronized (lock) {
            value = 42;   // 写操作
        } // unlock happens-before 后续的 lock

        synchronized (lock) {
            System.out.println(value); // 能看到 value = 42
        }
    }

    // 示例3：volatile变量规则
    public void volatileRule() {
        flag = true;      // volatile写 - happens-before 后续的volatile读
        if (flag) {       // volatile读 - 能看到上面的写入
            System.out.println("Flag is true");
        }
    }

    // 示例4：线程启动规则
    public void threadStartRule() {
        value = 100;      // 1
        Thread thread = new Thread(() -> {
            System.out.println(value); // 2 - 能看到 value = 100
        });
        thread.start();   // start() happens-before 线程中的动作
    }

    // 示例5：传递性规则
    public void transitivityRule() {
        // A happens-before B
        synchronized (lock) {
            value = 200;  // A
        }

        // B happens-before C
        Thread thread = new Thread(() -> {
            synchronized (lock) {
                System.out.println(value); // C - 能看到 value = 200
            }
        });
        thread.start(); // 启动线程
    }
}

可见性问题实战

1. 可见性问题演示

1.1 经典的可见性问题

/**
 * 可见性问题演示：子线程可能永远看不到主线程对flag的修改
 */
public class VisibilityProblem {

    // 如果不加volatile，子线程可能永远看不到flag的变化
    private static boolean flag = false;

    public static void main(String[] args) throws InterruptedException {
        System.out.println("=== 可见性问题演示 ===");

        // 创建子线程
        Thread workerThread = new Thread(() -> {
            System.out.println("子线程启动，开始监控flag...");
            int localCount = 0;

            while (!flag) {  // 如果没有volatile，可能无限循环
                localCount++;
                // 偶尔打印，避免控制台刷屏
                if (localCount % 100_000_000 == 0) {
                    System.out.println("子线程仍在循环，计数: " + localCount);
                }
            }

            System.out.println("子线程检测到flag = true，退出循环");
            System.out.println("子线程最终计数: " + localCount);
        }, "Worker-Thread");

        workerThread.start();

        // 主线程休眠1秒后修改flag
        Thread.sleep(1000);
        System.out.println("主线程将设置 flag = true");
        flag = true;
        System.out.println("主线程已设置 flag = true");

        // 再等待2秒，看子线程是否能正常退出
        Thread.sleep(2000);

        if (workerThread.isAlive()) {
            System.out.println("警告：子线程仍在运行，可能存在可见性问题！");
            // 强制中断（仅用于演示）
            workerThread.interrupt();
        } else {
            System.out.println("子线程已正常退出");
        }
    }
}

1.2 深度分析：为什么会出现可见性问题？

/**
 * 深度分析可见性问题的根源
 */
public class VisibilityAnalysis {

    // 模拟缓存行和内存一致性问题
    private static class SharedData {
        // 不使用volatile，模拟缓存一致性协议失效
        public int counter = 0;
        public boolean ready = false;

        // 使用volatile，确保可见性
        public volatile boolean volatileReady = false;
    }

    private static final SharedData data = new SharedData();

    public static void main(String[] args) throws InterruptedException {
        System.out.println("=== 可见性问题深度分析 ===");

        // 测试1：无volatile的情况
        System.out.println("n--- 测试1：无volatile修饰的变量 ---");
        testWithoutVolatile();

        Thread.sleep(1000);

        // 测试2：有volatile的情况
        System.out.println("n--- 测试2：使用volatile修饰的变量 ---");
        testWithVolatile();
    }

    private static void testWithoutVolatile() throws InterruptedException {
        data.ready = false;
        data.counter = 0;

        Thread writerThread = new Thread(() -> {
            try {
                Thread.sleep(500); // 确保读取线程先开始
                data.counter = 100;
                data.ready = true;
                System.out.println("写入线程：ready = true, counter = 100");
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        }, "Writer-Thread");

        Thread readerThread = new Thread(() -> {
            int localCount = 0;
            while (!data.ready) {
                localCount++;
                // 空循环，依赖CPU缓存中的ready值
            }
            System.out.println("读取线程：检测到ready = true");
            System.out.println("读取线程：counter = " + data.counter +
                             " (可能看不到更新后的值)");
        }, "Reader-Thread");

        readerThread.start();
        writerThread.start();

        // 设置超时，避免无限等待
        readerThread.join(3000);
        if (readerThread.isAlive()) {
            System.out.println("读取线程超时，可能存在可见性问题");
            readerThread.interrupt();
        }
    }

    private static void testWithVolatile() throws InterruptedException {
        data.volatileReady = false;
        data.counter = 0;

        Thread writerThread = new Thread(() -> {
            try {
                Thread.sleep(500);
                data.counter = 200;
                data.volatileReady = true;
                System.out.println("写入线程：volatileReady = true, counter = 200");
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        }, "Volatile-Writer");

        Thread readerThread = new Thread(() -> {
            int localCount = 0;
            while (!data.volatileReady) {
                localCount++;
            }
            System.out.println("读取线程：检测到volatileReady = true");
            System.out.println("读取线程：counter = " + data.counter +
                             " (应该能看到更新后的值)");
        }, "Volatile-Reader");

        readerThread.start();
        writerThread.start();

        readerThread.join(3000);
        if (readerThread.isAlive()) {
            System.out.println("读取线程超时，这不应该发生");
            readerThread.interrupt();
        } else {
            System.out.println("读取线程正常退出，volatile保证了可见性");
        }
    }
}

2. volatile 关键字深度解析

2.1 volatile 的基本使用

/**
 * volatile关键字的基本使用和特性演示
 */
public class VolatileBasics {

    // volatile变量：保证可见性和有序性，但不保证原子性
    private volatile boolean flag = false;
    private volatile int counter = 0;

    // 非volatile变量：用于对比
    private boolean normalFlag = false;
    private int normalCounter = 0;

    public static void main(String[] args) throws InterruptedException {
        VolatileBasics demo = new VolatileBasics();

        System.out.println("=== volatile关键字基础演示 ===");

        // 测试1：volatile保证可见性
        demo.testVisibility();

        Thread.sleep(1000);

        // 测试2：volatile不保证原子性
        demo.testAtomicity();

        Thread.sleep(1000);

        // 测试3：volatile防止指令重排序
        demo.testOrdering();
    }

    // 测试可见性
    private void testVisibility() throws InterruptedException {
        System.out.println("n--- 测试1：volatile可见性保证 ---");

        Thread writer = new Thread(() -> {
            try {
                Thread.sleep(500);
                flag = true;
                normalFlag = true;
                System.out.println("写入线程：设置 flag = true, normalFlag = true");
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        });

        Thread volatileReader = new Thread(() -> {
            int count = 0;
            while (!flag) {
                count++;
            }
            System.out.println("volatile读取线程：检测到flag = true，循环次数: " + count);
        });

        Thread normalReader = new Thread(() -> {
            int count = 0;
            while (!normalFlag) {
                count++;
            }
            System.out.println("普通读取线程：检测到normalFlag = true，循环次数: " + count);
        });

        volatileReader.start();
        normalReader.start();
        writer.start();

        volatileReader.join(2000);
        normalReader.join(2000);

        if (volatileReader.isAlive()) {
            volatileReader.interrupt();
            System.out.println("volatile读取线程超时（不应该发生）");
        }

        if (normalReader.isAlive()) {
            normalReader.interrupt();
            System.out.println("普通读取线程超时（可能发生）");
        }
    }

    // 测试原子性（演示volatile不能保证原子性）
    private void testAtomicity() throws InterruptedException {
        System.out.println("n--- 测试2：volatile不能保证原子性 ---");

        final int THREAD_COUNT = 10;
        final int INCREMENTS_PER_THREAD = 1000;
        Thread[] threads = new Thread[THREAD_COUNT];

        // 重置计数器
        counter = 0;
        normalCounter = 0;

        // 创建多个线程增加volatile计数器
        for (int i = 0; i < THREAD_COUNT; i++) {
            threads[i] = new Thread(() -> {
                for (int j = 0; j < INCREMENTS_PER_THREAD; j++) {
                    counter++;  // 非原子操作：读取-修改-写入
                    normalCounter++;
                }
            });
        }

        // 启动所有线程
        for (Thread thread : threads) {
            thread.start();
        }

        // 等待所有线程完成
        for (Thread thread : threads) {
            thread.join();
        }

        int expectedCount = THREAD_COUNT * INCREMENTS_PER_THREAD;
        System.out.println("预期计数: " + expectedCount);
        System.out.println("volatile计数器实际值: " + counter);
        System.out.println("普通计数器实际值: " + normalCounter);
        System.out.println("volatile计数器是否正确: " + (counter == expectedCount));
        System.out.println("普通计数器是否正确: " + (normalCounter == expectedCount));
    }

    // 测试有序性（防止指令重排序）
    private void testOrdering() {
        System.out.println("n--- 测试3：volatile防止指令重排序 ---");

        // 这个例子演示了volatile如何防止指令重排序
        // 在单例模式的懒汉式中，volatile是必需的
        Singleton instance1 = Singleton.getInstance();
        Singleton instance2 = Singleton.getInstance();

        System.out.println("单例模式测试完成");
        System.out.println("实例1是否等于实例2: " + (instance1 == instance2));
    }

    // 演示volatile在单例模式中的应用
    private static class Singleton {
        private static volatile Singleton instance;

        private Singleton() {
            // 防止反射创建实例
            if (instance != null) {
                throw new IllegalStateException("Singleton already initialized");
            }
        }

        public static Singleton getInstance() {
            if (instance == null) {  // 第一次检查
                synchronized (Singleton.class) {
                    if (instance == null) {  // 第二次检查
                        instance = new Singleton();
                    }
                }
            }
            return instance;
        }
    }
}

2.2 volatile 的底层实现原理

/**
 * volatile底层实现原理演示和分析
 */
public class VolatileImplementation {

    // volatile变量
    private volatile int volatileVar = 0;

    // 普通变量
    private int normalVar = 0;

    public static void main(String[] args) throws InterruptedException {
        System.out.println("=== volatile底层实现原理分析 ===");

        VolatileImplementation demo = new VolatileImplementation();

        // 演示内存屏障的效果
        demo.testMemoryBarriers();

        Thread.sleep(500);

        // 演示缓存一致性协议
        demo.testCacheCoherence();
    }

    // 测试内存屏障的效果
    private void testMemoryBarriers() throws InterruptedException {
        System.out.println("n--- 内存屏障效果演示 ---");

        // 设置变量
        volatileVar = 1;
        normalVar = 1;

        Thread reader1 = new Thread(() -> {
            int value1 = volatileVar;  // LoadLoad屏障
            int value2 = normalVar;    // 可能被重排序到volatileVar读取之前
            System.out.println("线程1读取：volatileVar=" + value1 + ", normalVar=" + value2);
        });

        Thread reader2 = new Thread(() -> {
            int value3 = normalVar;    // 普通读取
            int value4 = volatileVar;  // LoadLoad屏障确保normalVar读取在volatileVar之前
            System.out.println("线程2读取：normalVar=" + value3 + ", volatileVar=" + value4);
        });

        reader1.start();
        reader2.start();

        reader1.join();
        reader2.join();

        System.out.println("内存屏障确保了volatile读操作的有序性");
    }

    // 测试缓存一致性协议
    private void testCacheCoherence() throws InterruptedException {
        System.out.println("n--- 缓存一致性协议演示 ---");

        final int ITERATIONS = 100;

        Thread writer = new Thread(() -> {
            for (int i = 1; i <= ITERATIONS; i++) {
                volatileVar = i;
                try {
                    Thread.sleep(10);
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    break;
                }
                if (i % 20 == 0) {
                    System.out.println("写入线程：volatileVar = " + i);
                }
            }
        });

        Thread reader = new Thread(() -> {
            int lastValue = 0;
            int readCount = 0;

            while (readCount < ITERATIONS) {
                int currentValue = volatileVar;
                if (currentValue != lastValue) {
                    readCount++;
                    lastValue = currentValue;
                    System.out.println("读取线程：检测到新值 " + currentValue +
                                     " (第" + readCount + "次读取)");
                }

                // 模拟其他工作
                try {
                    Thread.sleep(5);
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    break;
                }
            }
        });

        writer.start();
        reader.start();

        writer.join();
        reader.join();

        System.out.println("缓存一致性协议确保了所有线程看到最新的volatile值");
    }
}

/**
 * volatile字节码分析助手
 */
public class VolatileBytecodeAnalysis {

    // 编译命令：javap -c VolatileBytecodeAnalysis
    public static void main(String[] args) {
        System.out.println("请使用 javap -c VolatileBytecodeAnalysis 查看字节码");
        System.out.println("对比volatile变量和普通变量的字节码差异");
    }

    private volatile int volatileField;
    private int normalField;

    public void writeVolatile() {
        volatileField = 1;  // 字节码中会有putfield指令，但JVM会插入内存屏障
    }

    public void writeNormal() {
        normalField = 1;    // 普通的putfield指令
    }

    public int readVolatile() {
        return volatileField;  // 字节码中会有getfield指令，但JVM会插入内存屏障
    }

    public int readNormal() {
        return normalField;    // 普通的getfield指令
    }
}

3. 指令重排序与内存屏障

3.1 指令重排序问题演示

/**
 * 指令重排序问题演示
 */
public class ReorderingProblem {

    private static int x = 0, y = 0;
    private static int a = 0, b = 0;

    public static void main(String[] args) throws InterruptedException {
        System.out.println("=== 指令重排序问题演示 ===");

        int reorderCount = 0;
        int totalTests = 1000000;

        for (int i = 0; i < totalTests; i++) {
            // 重置变量
            x = y = a = b = 0;

            // 创建两个线程
            Thread t1 = new Thread(() -> {
                a = 1;  // 操作1
                x = b;  // 操作2 - 可能被重排序到操作1之前
            });

            Thread t2 = new Thread(() -> {
                b = 1;  // 操作3
                y = a;  // 操作4 - 可能被重排序到操作3之前
            });

            t1.start();
            t2.start();

            t1.join();
            t2.join();

            // 检查是否发生了指令重排序
            if (x == 0 && y == 0) {
                reorderCount++;
                System.out.println("第" + (i + 1) + "次测试检测到指令重排序！x=" + x + ", y=" + y);

                // 只显示前几次
                if (reorderCount >= 5) {
                    break;
                }
            }
        }

        System.out.println("总测试次数: " + Math.min(totalTests, reorderCount == 0 ? totalTests : 5000));
        System.out.println("检测到重排序次数: " + reorderCount);

        if (reorderCount > 0) {
            System.out.println("指令重排序确实发生了！这说明需要内存屏障来保证有序性。");
        } else {
            System.out.println("在当前测试中未检测到明显的指令重排序（可能需要更多测试）");
        }
    }
}

3.2 内存屏障的详细分析

/**
 * 内存屏障详细分析和演示
 */
public class MemoryBarrierAnalysis {

    // 使用volatile来演示内存屏障的插入
    private volatile boolean flag = false;
    private int data = 0;
    private int ready = 0;

    public static void main(String[] args) throws InterruptedException {
        MemoryBarrierAnalysis demo = new MemoryBarrierAnalysis();

        System.out.println("=== 内存屏障详细分析 ===");

        // 演示不同类型的内存屏障
        demo.demoLoadLoadBarriers();

        Thread.sleep(500);

        demo.demoStoreStoreBarriers();

        Thread.sleep(500);

        demo.demoLoadStoreBarriers();

        Thread.sleep(500);

        demo.demoStoreLoadBarriers();
    }

    // LoadLoad屏障演示
    private void demoLoadLoadBarriers() throws InterruptedException {
        System.out.println("n--- LoadLoad屏障演示 ---");
        System.out.println("LoadLoad屏障：确保Load1的读取操作先于Load2及后续读取操作");

        data = 42;
        flag = true;  // volatile写

        Thread reader = new Thread(() -> {
            // LoadLoad屏障在这里插入（由volatile读触发）
            boolean flagValue = flag;  // Load1
            int dataValue = data;      // Load2 - 确保在Load1之后

            System.out.println("LoadLoad屏障效果：flag=" + flagValue + ", data=" + dataValue);
            System.out.println("确保了data的读取在flag读取之后进行");
        });

        reader.start();
        reader.join();
    }

    // StoreStore屏障演示
    private void demoStoreStoreBarriers() throws InterruptedException {
        System.out.println("n--- StoreStore屏障演示 ---");
        System.out.println("StoreStore屏障：确保Store1立刻对其他处理器可见，先于Store2及后续存储");

        Thread writer = new Thread(() -> {
            data = 100;     // Store1
            // StoreStore屏障在这里插入（由volatile写触发）
            ready = 1;      // Store2 - volatile写

            System.out.println("StoreStore屏障确保data=100的写入对ready=1的写入之前可见");
        });

        Thread observer = new Thread(() -> {
            while (ready != 1) {
                Thread.yield();
            }
            int dataValue = data;
            System.out.println("观察者线程看到ready=1，data=" + dataValue +
                             " (应该能看到data=100)");
        });

        observer.start();
        writer.start();

        writer.join();
        observer.join();
    }

    // LoadStore屏障演示
    private void demoLoadStoreBarriers() throws InterruptedException {
        System.out.println("n--- LoadStore屏障演示 ---");
        System.out.println("LoadStore屏障：确保Load1数据装载先于Store2及后续存储刷新到内存");

        flag = false;  // 重置
        data = 0;

        Thread processor = new Thread(() -> {
            boolean flagValue = flag;  // Load1
            // LoadStore屏障在这里插入
            data = 200;               // Store1 - 确保在Load之后

            System.out.println("LoadStore屏障：先读取flag，后写入data");
        });

        Thread flagSetter = new Thread(() -> {
            try {
                Thread.sleep(100);
                flag = true;  // 设置flag
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        });

        flagSetter.start();
        processor.start();

        processor.join();
        flagSetter.join();
    }

    // StoreLoad屏障演示
    private void demoStoreLoadBarriers() throws InterruptedException {
        System.out.println("n--- StoreLoad屏障演示 ---");
        System.out.println("StoreLoad屏障：确保Store1立刻对其他处理器可见，先于Load2及后续装载");

        final boolean[] stopFlag = {false};

        Thread writer = new Thread(() -> {
            int counter = 0;
            while (!stopFlag[0]) {
                counter++;
                data = counter;      // Store1
                // StoreLoad屏障在这里插入（由volatile读写触发）
                boolean currentFlag = flag; // Load1

                if (counter % 100000 == 0) {
                    System.out.println("写入线程：data=" + counter + ", flag=" + currentFlag);
                }
            }
        });

        Thread reader = new Thread(() -> {
            try {
                Thread.sleep(100);
                flag = true;  // volatile写
                Thread.sleep(100);
                stopFlag[0] = true;
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        });

        writer.start();
        reader.start();

        writer.join();
        reader.join();

        System.out.println("StoreLoad屏障确保存储操作对后续加载操作可见");
    }
}

实战练习

1. 基础练习 ⭐

任务: 使用 volatile 解决简单的可见性问题

/**
 * 基础练习：使用volatile解决可见性问题
 */
public class BasicExercise {

    // 任务1：使用volatile修复可见性问题
    private volatile boolean shutdownRequested = false;

    // 任务2：使用volatile实现简单的状态机
    private volatile String currentState = "INIT";

    public static void main(String[] args) throws InterruptedException {
        BasicExercise exercise = new BasicExercise();

        System.out.println("=== 基础练习：volatile可见性问题 ===");

        // 练习1：优雅停止线程
        exercise.exercise1_GracefulShutdown();

        Thread.sleep(1000);

        // 练习2：状态通知
        exercise.exercise2_StateNotification();
    }

    // 练习1：优雅停止线程
    private void exercise1_GracefulShutdown() throws InterruptedException {
        System.out.println("n--- 练习1：优雅停止工作线程 ---");

        Thread worker = new Thread(() -> {
            System.out.println("工作线程开始运行...");
            int taskCount = 0;

            while (!shutdownRequested) {
                taskCount++;

                // 模拟工作
                try {
                    Thread.sleep(100);
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    break;
                }

                // 定期报告状态
                if (taskCount % 10 == 0) {
                    System.out.println("工作线程：已完成 " + taskCount + " 个任务");
                }
            }

            System.out.println("工作线程：收到停止信号，正在清理资源...");
            try {
                Thread.sleep(200); // 模拟清理工作
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
            System.out.println("工作线程：已停止，总共处理了 " + taskCount + " 个任务");
        }, "Worker-Thread");

        worker.start();

        // 主线程运行一段时间后请求停止
        Thread.sleep(2000);
        System.out.println("主线程：请求停止工作线程");
        shutdownRequested = true;

        worker.join(1000);
        if (worker.isAlive()) {
            System.out.println("主线程：工作线程未及时响应，强制中断");
            worker.interrupt();
        } else {
            System.out.println("主线程：工作线程已优雅停止");
        }
    }

    // 练习2：状态通知
    private void exercise2_StateNotification() throws InterruptedException {
        System.out.println("n--- 练习2：基于volatile的状态通知 ---");

        String[] states = {"INIT", "READY", "PROCESSING", "COMPLETED"};

        Thread stateMonitor = new Thread(() -> {
            String lastState = "";
            while (!"COMPLETED".equals(currentState)) {
                if (!currentState.equals(lastState)) {
                    lastState = currentState;
                    System.out.println("状态监控器：检测到状态变化 -> " + lastState);
                }

                try {
                    Thread.sleep(50);
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    break;
                }
            }
            System.out.println("状态监控器：处理已完成");
        }, "State-Monitor");

        Thread stateChanger = new Thread(() -> {
            try {
                for (String state : states) {
                    currentState = state;
                    System.out.println("状态设置器：设置状态为 " + state);
                    Thread.sleep(300);
                }
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        }, "State-Changer");

        stateMonitor.start();
        stateChanger.start();

        stateChanger.join();
        stateMonitor.join();

        System.out.println("练习2完成：状态通知机制工作正常");
    }
}

2. 进阶练习 ⭐⭐

任务: 实现一个基于 volatile 的自旋锁

/**
 * 进阶练习：基于volatile的自旋锁实现
 */
public class AdvancedExercise {

    public static void main(String[] args) throws InterruptedException {
        System.out.println("=== 进阶练习：volatile自旋锁 ===");

        // 测试自旋锁
        testSpinLock();

        Thread.sleep(1000);

        // 测试可重入自旋锁
        testReentrantSpinLock();
    }

    // 测试基础自旋锁
    private static void testSpinLock() throws InterruptedException {
        System.out.println("n--- 测试基础自旋锁 ---");

        SpinLock spinLock = new SpinLock();
        AtomicInteger counter = new AtomicInteger(0);
        int threadCount = 5;
        int incrementsPerThread = 1000;
        CountDownLatch latch = new CountDownLatch(threadCount);

        // 创建多个线程竞争锁
        for (int i = 0; i < threadCount; i++) {
            final int threadId = i;
            new Thread(() -> {
                try {
                    for (int j = 0; j < incrementsPerThread; j++) {
                        spinLock.lock();
                        try {
                            // 临界区：简单计数
                            counter.incrementAndGet();

                            // 模拟一些工作
                            Thread.sleep(1);
                        } finally {
                            spinLock.unlock();
                        }
                    }
                    System.out.println("线程 " + threadId + " 完成");
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                } finally {
                    latch.countDown();
                }
            }, "SpinLock-Thread-" + i).start();
        }

        latch.await();
        System.out.println("所有线程完成，最终计数: " + counter.get());
        System.out.println("预期计数: " + (threadCount * incrementsPerThread));
        System.out.println("计数正确: " + (counter.get() == threadCount * incrementsPerThread));
    }

    // 测试可重入自旋锁
    private static void testReentrantSpinLock() throws InterruptedException {
        System.out.println("n--- 测试可重入自旋锁 ---");

        ReentrantSpinLock reentrantLock = new ReentrantSpinLock();
        AtomicInteger recursiveCounter = new AtomicInteger(0);

        Thread recursiveThread = new Thread(() -> {
            reentrantLock.lock();
            try {
                System.out.println("外层锁获取成功");

                reentrantLock.lock();
                try {
                    System.out.println("内层锁获取成功");

                    reentrantLock.lock();
                    try {
                        System.out.println("最内层锁获取成功");
                        recursiveCounter.set(100);
                    } finally {
                        reentrantLock.unlock();
                        System.out.println("最内层锁释放");
                    }
                } finally {
                    reentrantLock.unlock();
                    System.out.println("内层锁释放");
                }
            } finally {
                reentrantLock.unlock();
                System.out.println("外层锁释放");
            }
        }, "Recursive-Thread");

        recursiveThread.start();
        recursiveThread.join();

        System.out.println("可重入测试完成，递归计数器值: " + recursiveCounter.get());
    }
}

/**
 * 基于volatile的简单自旋锁实现
 */
class SpinLock {
    private volatile boolean locked = false;

    public void lock() {
        // 自旋直到获取锁
        while (locked) {
            // 自旋等待
            Thread.onSpinWait(); // Java 9+ 提示处理器进入自旋等待状态
        }

        // 设置锁状态
        locked = true;
    }

    public void unlock() {
        locked = false;
    }
}

/**
 * 基于volatile的可重入自旋锁实现
 */
class ReentrantSpinLock {
    private volatile Thread owner = null;
    private volatile int recursionCount = 0;

    public void lock() {
        Thread currentThread = Thread.currentThread();

        // 如果已经持有锁，增加重入计数
        if (owner == currentThread) {
            recursionCount++;
            return;
        }

        // 自旋直到获取锁
        while (owner != null) {
            Thread.onSpinWait();
        }

        // 获取锁
        owner = currentThread;
        recursionCount = 1;
    }

    public void unlock() {
        Thread currentThread = Thread.currentThread();

        if (owner != currentThread) {
            throw new IllegalStateException("当前线程未持有锁");
        }

        recursionCount--;

        if (recursionCount == 0) {
            owner = null;
        }
    }
}

3. 挑战练习 ⭐⭐⭐

任务: 实现一个高性能的缓存系统，使用 volatile 保证数据一致性

import java.util.concurrent.*;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicReference;

/**
 * 挑战练习：高性能缓存系统实现
 */
public class ChallengeExercise {

    public static void main(String[] args) throws InterruptedException {
        System.out.println("=== 挑战练习：高性能缓存系统 ===");

        // 测试缓存系统
        testCacheSystem();

        Thread.sleep(1000);

        // 性能测试
        performanceTest();
    }

    // 基础功能测试
    private static void testCacheSystem() throws InterruptedException {
        System.out.println("n--- 缓存系统功能测试 ---");

        CacheSystem<String, String> cache = new CacheSystem<>();

        // 测试基本的put/get操作
        cache.put("key1", "value1");
        cache.put("key2", "value2");

        System.out.println("获取key1: " + cache.get("key1"));
        System.out.println("获取key2: " + cache.get("key2"));
        System.out.println("获取不存在的key: " + cache.get("nonexistent"));

        // 测试并发访问
        int threadCount = 10;
        int operationsPerThread = 100;
        CountDownLatch latch = new CountDownLatch(threadCount);
        AtomicInteger successCount = new AtomicInteger(0);
        AtomicInteger missCount = new AtomicInteger(0);

        for (int i = 0; i < threadCount; i++) {
            final int threadId = i;
            new Thread(() -> {
                try {
                    for (int j = 0; j < operationsPerThread; j++) {
                        String key = "key" + (threadId * 10 + j % 10);
                        String value = "value" + j;

                        // 尝试获取
                        String cachedValue = cache.get(key);
                        if (cachedValue == null) {
                            // 缓存未命中，放入缓存
                            cache.put(key, value);
                            missCount.incrementAndGet();
                        } else {
                            // 缓存命中
                            successCount.incrementAndGet();
                        }

                        // 模拟一些处理时间
                        if (j % 20 == 0) {
                            Thread.sleep(1);
                        }
                    }
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                } finally {
                    latch.countDown();
                }
            }, "Cache-Thread-" + i).start();
        }

        latch.await();

        System.out.println("并发测试完成:");
        System.out.println("缓存命中次数: " + successCount.get());
        System.out.println("缓存未命中次数: " + missCount.get());
        System.out.println("缓存命中率: " +
                         String.format("%.2f%%",
                             (double) successCount.get() / (successCount.get() + missCount.get()) * 100));

        // 测试缓存统计
        CacheStats stats = cache.getStats();
        System.out.println("缓存统计: " + stats);
    }

    // 性能测试
    private static void performanceTest() throws InterruptedException {
        System.out.println("n--- 性能测试 ---");

        CacheSystem<Integer, String> cache = new CacheSystem<>();
        int threadCount = 20;
        int operationsPerThread = 10000;

        System.out.println("启动 " + threadCount + " 个线程，每个执行 " + operationsPerThread + " 次操作");

        long startTime = System.nanoTime();
        CountDownLatch latch = new CountDownLatch(threadCount);

        for (int i = 0; i < threadCount; i++) {
            final int threadId = i;
            new Thread(() -> {
                try {
                    for (int j = 0; j < operationsPerThread; j++) {
                        int key = threadId * 1000 + (j % 1000);
                        String value = "value-" + key;

                        // 随机操作：70%读取，30%写入
                        if (Math.random() < 0.7) {
                            cache.get(key);
                        } else {
                            cache.put(key, value);
                        }
                    }
                } finally {
                    latch.countDown();
                }
            }, "Perf-Thread-" + i).start();
        }

        latch.await();
        long endTime = System.nanoTime();

        long totalOperations = threadCount * operationsPerThread;
        double duration = (endTime - startTime) / 1_000_000.0; // 毫秒
        double opsPerSecond = totalOperations / (duration / 1000.0);

        System.out.println("性能测试结果:");
        System.out.println("总操作数: " + totalOperations);
        System.out.println("总耗时: " + String.format("%.2f", duration) + " ms");
        System.out.println("吞吐量: " + String.format("%.0f", opsPerSecond) + " ops/sec");

        CacheStats finalStats = cache.getStats();
        System.out.println("最终缓存统计: " + finalStats);
    }
}

/**
 * 高性能缓存系统实现
 */
class CacheSystem<K, V> {

    // 使用volatile保证缓存状态的可见性
    private volatile CacheEntry<K, V>[] table;
    private volatile int size;
    private volatile int modCount;

    // 统计信息
    private final AtomicInteger hitCount = new AtomicInteger(0);
    private final AtomicInteger missCount = new AtomicInteger(0);
    private final AtomicInteger putCount = new AtomicInteger(0);

    // 缓存配置
    private static final int DEFAULT_CAPACITY = 16;
    private static final float LOAD_FACTOR = 0.75f;
    private final int capacity;

    @SuppressWarnings("unchecked")
    public CacheSystem() {
        this.capacity = DEFAULT_CAPACITY;
        this.table = new CacheEntry[capacity];
        this.size = 0;
        this.modCount = 0;
    }

    public void put(K key, V value) {
        if (key == null) {
            throw new IllegalArgumentException("Key cannot be null");
        }

        int index = getIndex(key);
        CacheEntry<K, V> entry = new CacheEntry<>(key, value);

        // 简单的线性探测处理冲突
        while (table[index] != null && !table[index].key.equals(key)) {
            index = (index + 1) % capacity;
        }

        if (table[index] == null) {
            size++;
        }

        table[index] = entry;
        putCount.incrementAndGet();
        modCount++;
    }

    public V get(K key) {
        if (key == null) {
            return null;
        }

        int index = getIndex(key);
        int startIndex = index;

        // 线性探测查找
        while (table[index] != null) {
            if (table[index].key.equals(key)) {
                hitCount.incrementAndGet();
                return table[index].value;
            }

            index = (index + 1) % capacity;
            if (index == startIndex) {
                break; // 遍历完整个表
            }
        }

        missCount.incrementAndGet();
        return null;
    }

    private int getIndex(K key) {
        return Math.abs(key.hashCode()) % capacity;
    }

    public CacheStats getStats() {
        int totalRequests = hitCount.get() + missCount.get();
        double hitRate = totalRequests == 0 ? 0.0 : (double) hitCount.get() / totalRequests;

        return new CacheStats(
            size,
            capacity,
            hitCount.get(),
            missCount.get(),
            putCount.get(),
            hitRate
        );
    }

    // 缓存条目
    private static class CacheEntry<K, V> {
        final K key;
        volatile V value;

        CacheEntry(K key, V value) {
            this.key = key;
            this.value = value;
        }
    }

    // 缓存统计信息
    public static class CacheStats {
        private final int size;
        private final int capacity;
        private final int hitCount;
        private final int missCount;
        private final int putCount;
        private final double hitRate;

        public CacheStats(int size, int capacity, int hitCount, int missCount,
                         int putCount, double hitRate) {
            this.size = size;
            this.capacity = capacity;
            this.hitCount = hitCount;
            this.missCount = missCount;
            this.putCount = putCount;
            this.hitRate = hitRate;
        }

        @Override
        public String toString() {
            return String.format(
                "CacheStats{size=%d, capacity=%d, hitCount=%d, missCount=%d, putCount=%d, hitRate=%.2f%%}",
                size, capacity, hitCount, missCount, putCount, hitRate * 100
            );
        }
    }
}

今日总结

核心要点回顾

1. Java 内存模型 (JMM) ：

   • 抽象了主内存和工作内存的概念
   • 定义了 8 种原子操作来管理内存交互
   • 为并发编程提供了规范保证

2. JMM 三大特性：

   • 原子性：操作不可分割（需要 synchronized 或 atomic 类保证）
   • 可见性：变量修改对其他线程立即可见（volatile 或 synchronized 保证）
   • 有序性：程序执行顺序与代码顺序一致（volatile 或 synchronized 保证）

3. volatile 关键字：

   • 保证可见性和有序性，但不保证原子性
   • 通过插入内存屏障来实现有序性保证
   • 基于 MESI 等缓存一致性协议实现可见性

4. happens-before 原则：

   • 定义了操作间的偏序关系
   • 是判断数据是否存在竞争、线程是否安全的重要依据
   • 8 大规则为并发编程提供了理论基础

5. 指令重排序与内存屏障：

   • 编译器和处理器可能会进行指令重排序优化
   • 内存屏障可以禁止特定类型重排序
   • volatile 读/写会插入相应的内存屏障

最佳实践建议

1. volatile 使用场景：

   • 状态标志位（如停止标志）
   • 双重检查锁定（DCL）中的实例变量
   • 独立观察者的发布场景
   • 读写锁的状态变量

2. 避免的陷阱：

   • 不要依赖 volatile 保证复合操作的原子性
   • 不要在 volatile 变量上进行递增或递减操作
   • 理解 volatile 的性能开销（相对 synchronized 较小）

3. 并发编程原则：

   • 优先使用不可变对象
   • 使用适当的同步机制（synchronized、volatile、atomic 类）
   • 理解 happens-before 关系，避免数据竞争

下节预告

明天我们将深入学习 线程生命周期与状态转换，包括：

• 线程的六大状态详解
• 线程控制方法：sleep、join、yield、interrupt
• 守护线程的特性与应用
• 线程状态监控和调试技巧

课后作业

1. 理论作业：

   • 详细解释 JMM 的内存交互过程
   • 分析 volatile 与 synchronized 的异同点
   • 列举 happens-before 的 8 大规则并举例说明

2. 实践作业：

   • 实现一个基于 volatile 的任务调度器
   • 优化之前的生产者-消费者代码，使用 volatile 优化性能
   • 分析一个开源项目中 volatile 的使用情况