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Zookeeper实现分布式锁实战应用示例

1. 分布式锁概述

在分布式系统中，当多个进程或服务需要互斥地访问共享资源时，就需要分布式锁来协调。Zookeeper因其强一致性和临时节点特性，非常适合实现分布式锁。

2. Zookeeper实现分布式锁的核心原理

• 临时顺序节点：创建的节点是临时的，客户端断开连接后自动删除
• 节点顺序性：Zookeeper会为节点名称添加递增序号
• 最小节点获取锁：所有客户端监听比自己序号小的节点，序号最小的获取锁
• 监听机制：通过Watcher机制实现锁释放通知

3. 实战代码示例（Java）

3.1 引入依赖

<dependency><groupId>org.apache.zookeeper</groupId><artifactId>zookeeper</artifactId><version>3.6.3</version>
</dependency>

3.2 分布式锁实现

import org.apache.zookeeper.*;
import org.apache.zookeeper.data.Stat;import java.io.IOException;
import java.util.Collections;
import java.util.List;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;public class ZkDistributedLock implements Watcher {private ZooKeeper zk;private String lockPath;private String currentLock;private String waitPath;private CountDownLatch latch;private CountDownLatch connectedLatch = new CountDownLatch(1);private static final String LOCK_ROOT = "/locks";private static final int SESSION_TIMEOUT = 30000;public ZkDistributedLock(String zkServers) throws IOException, InterruptedException, KeeperException {zk = new ZooKeeper(zkServers, SESSION_TIMEOUT, this);connectedLatch.await();// 确保根节点存在Stat stat = zk.exists(LOCK_ROOT, false);if (stat == null) {zk.create(LOCK_ROOT, new byte[0], ZooDefs.Ids.OPEN_ACL_UNSAFE, CreateMode.PERSISTENT);}}@Overridepublic void process(WatchedEvent event) {if (event.getState() == Event.KeeperState.SyncConnected) {connectedLatch.countDown();}if (this.latch != null && event.getType() == Event.EventType.NodeDeleted) {this.latch.countDown();}}public boolean tryLock() throws KeeperException, InterruptedException {// 创建临时顺序节点currentLock = zk.create(LOCK_ROOT + "/lock_", new byte[0], ZooDefs.Ids.OPEN_ACL_UNSAFE, CreateMode.EPHEMERAL_SEQUENTIAL);// 获取所有子节点List<String> children = zk.getChildren(LOCK_ROOT, false);Collections.sort(children);// 当前节点是最小节点，则获取锁if (currentLock.equals(LOCK_ROOT + "/" + children.get(0))) {return true;}// 不是最小节点，找到前一个节点int currentIndex = Collections.binarySearch(children, currentLock.substring(LOCK_ROOT.length() + 1));waitPath = LOCK_ROOT + "/" + children.get(currentIndex - 1);// 监听前一个节点Stat stat = zk.exists(waitPath, true);if (stat != null) {this.latch = new CountDownLatch(1);this.latch.await();this.latch = null;}return true;}public boolean tryLock(long timeout, TimeUnit unit) throws Exception {long start = System.currentTimeMillis();long end = start + unit.toMillis(timeout);while (System.currentTimeMillis() < end) {if (tryLock()) {return true;}Thread.sleep(100);}return false;}public void unlock() throws KeeperException, InterruptedException {zk.delete(currentLock, -1);currentLock = null;if (zk != null) {zk.close();}}
}

3.3 使用示例

public class DistributedLockExample {public static void main(String[] args) {String zkServers = "localhost:2181";String resourceKey = "order_123";for (int i = 0; i < 5; i++) {new Thread(() -> {ZkDistributedLock lock = null;try {lock = new ZkDistributedLock(zkServers);System.out.println(Thread.currentThread().getName() + " 尝试获取锁");if (lock.tryLock(5, TimeUnit.SECONDS)) {System.out.println(Thread.currentThread().getName() + " 获取锁成功");// 模拟业务处理Thread.sleep(2000);} else {System.out.println(Thread.currentThread().getName() + " 获取锁超时");}} catch (Exception e) {e.printStackTrace();} finally {if (lock != null) {try {lock.unlock();System.out.println(Thread.currentThread().getName() + " 释放锁");} catch (Exception e) {e.printStackTrace();}}}}, "Thread-" + i).start();}}
}

4. 实际应用场景

4.1 电商秒杀系统

public class SeckillService {private ZkDistributedLock lock;public SeckillService(String zkServers) throws Exception {this.lock = new ZkDistributedLock(zkServers);}public boolean seckill(String productId, String userId) {try {if (lock.tryLock(3, TimeUnit.SECONDS)) {// 1. 查询库存int stock = getStockFromDB(productId);if (stock <= 0) {return false;}// 2. 扣减库存reduceStock(productId);// 3. 创建订单createOrder(productId, userId);return true;}return false;} catch (Exception e) {e.printStackTrace();return false;} finally {try {lock.unlock();} catch (Exception e) {e.printStackTrace();}}}// 其他方法...
}

4.2 分布式定时任务

public class DistributedScheduler {private ZkDistributedLock lock;public DistributedScheduler(String zkServers) throws Exception {this.lock = new ZkDistributedLock(zkServers);}public void scheduleTask() {try {if (lock.tryLock(0, TimeUnit.SECONDS)) {// 只有获取锁的节点执行任务executeTask();}} catch (Exception e) {e.printStackTrace();} finally {try {lock.unlock();} catch (Exception e) {e.printStackTrace();}}}private void executeTask() {// 执行定时任务逻辑System.out.println("执行定时任务: " + new Date());}
}

5. 优化与注意事项

1. 锁重入问题：如果需要支持同一线程重入，需要额外记录线程信息
2. 锁等待队列：公平锁实现需要考虑等待队列的顺序
3. 超时处理：合理设置锁获取超时时间，避免死锁
4. 连接恢复：处理Zookeeper连接断开后的重连机制
5. 锁释放：确保锁最终能被释放，避免死锁
6. 性能考虑：高频锁操作场景下，Zookeeper可能成为性能瓶颈

6. 其他实现方案对比

1. Curator框架：Apache Curator提供了更高级的分布式锁实现

   InterProcessMutex lock = new InterProcessMutex(client, "/lock_path");
   lock.acquire();
   try {// 业务逻辑
   } finally {lock.release();
   }
   

2. Redis分布式锁：基于SETNX命令实现，性能更高但一致性较弱

3. 数据库分布式锁：基于唯一索引或乐观锁实现，简单但性能较差

Zookeeper分布式锁适合对一致性要求高的场景，而Redis分布式锁适合高性能但对一致性要求相对宽松的场景。