引言
ZooKeeper是一个分布式的,开放源码的分布式应用程序协调服务,是Google的Chubby一个开源的实现,是Hadoop和Hbase的重要组件。它是一个为分布式应用提供一致性服务的软件,提供的功能包括:配置维护、域名服务、分布式同步、组服务等。
ZooKeeper的架构通过冗余服务实现高可用性。因此,如果第一次无应答,客户端就可以询问另一台ZooKeeper主机。ZooKeeper节点将它们的数据存储于一个分层的命名空间,非常类似于一个文件系统或一个前缀树结构。客户端可以在节点读写,从而以这种方式拥有一个共享的配置服务。更新是全序的。
基于ZooKeeper分布式锁的流程
- 在zookeeper指定节点(locks)下创建临时顺序节点node_n
- 获取locks下所有子节点children
- 对子节点按节点自增序号从小到大排序
- 判断本节点是不是第一个子节点,若是,则获取锁;若不是,则监听比该节点小的那个节点的删除事件
- 若监听事件生效,则回到第二步重新进行判断,直到获取到锁
具体实现
下面就具体使用java和zookeeper实现分布式锁,操作zookeeper使用的是apache提供的zookeeper的包。
- 通过实现Watch接口,实现process(WatchedEvent event)方法来实施监控,使CountDownLatch来完成监控,在等待锁的时候使用CountDownLatch来计数,等到后进行countDown,停止等待,继续运行。
- 以下整体流程基本与上述描述流程一致,只是在监听的时候使用的是CountDownLatch来监听前一个节点。
分布式锁
import org.apache.zookeeper.*; import org.apache.zookeeper.data.Stat; import java.io.IOException; import java.util.ArrayList; import java.util.Collections; import java.util.List; import java.util.concurrent.CountDownLatch; import java.util.concurrent.TimeUnit; import java.util.concurrent.locks.Condition; import java.util.concurrent.locks.Lock; /** * Created by liuyang on 2017/4/20. */ public class DistributedLock implements Lock, Watcher { private ZooKeeper zk = null; // 根节点 private String ROOT_LOCK = "/locks"; // 竞争的资源 private String lockName; // 等待的前一个锁 private String WAIT_LOCK; // 当前锁 private String CURRENT_LOCK; // 计数器 private CountDownLatch countDownLatch; private int sessionTimeout = 30000; private List<Exception> exceptionList = new ArrayList<Exception>(); /** * 配置分布式锁 * @param config 连接的url * @param lockName 竞争资源 */ public DistributedLock(String config, String lockName) { this.lockName = lockName; try { // 连接zookeeper zk = new ZooKeeper(config, sessionTimeout, this); Stat stat = zk.exists(ROOT_LOCK, false); if (stat == null) { // 如果根节点不存在,则创建根节点 zk.create(ROOT_LOCK, new byte[0], ZooDefs.Ids.OPEN_ACL_UNSAFE, CreateMode.PERSISTENT); } } catch (IOException e) { e.printStackTrace(); } catch (InterruptedException e) { e.printStackTrace(); } catch (KeeperException e) { e.printStackTrace(); } } // 节点监视器 public void process(WatchedEvent event) { if (this.countDownLatch != null) { this.countDownLatch.countDown(); } } public void lock() { if (exceptionList.size() > 0) { throw new LockException(exceptionList.get(0)); } try { if (this.tryLock()) { System.out.println(Thread.currentThread().getName() + " " + lockName + "获得了锁"); return; } else { // 等待锁 waitForLock(WAIT_LOCK, sessionTimeout); } } catch (InterruptedException e) { e.printStackTrace(); } catch (KeeperException e) { e.printStackTrace(); } } public boolean tryLock() { try { String splitStr = "_lock_"; if (lockName.contains(splitStr)) { throw new LockException("锁名有误"); } // 创建临时有序节点 CURRENT_LOCK = zk.create(ROOT_LOCK + "/" + lockName + splitStr, new byte[0], ZooDefs.Ids.OPEN_ACL_UNSAFE, CreateMode.EPHEMERAL_SEQUENTIAL); System.out.println(CURRENT_LOCK + " 已经创建"); // 取所有子节点 List<String> subNodes = zk.getChildren(ROOT_LOCK, false); // 取出所有lockName的锁 List<String> lockObjects = new ArrayList<String>(); for (String node : subNodes) { String _node = node.split(splitStr)[0]; if (_node.equals(lockName)) { lockObjects.add(node); } } Collections.sort(lockObjects); System.out.println(Thread.currentThread().getName() + " 的锁是 " + CURRENT_LOCK); // 若当前节点为最小节点,则获取锁成功 if (CURRENT_LOCK.equals(ROOT_LOCK + "/" + lockObjects.get(0))) { return true; } // 若不是最小节点,则找到自己的前一个节点 String prevNode = CURRENT_LOCK.substring(CURRENT_LOCK.lastIndexOf("/") + 1); WAIT_LOCK = lockObjects.get(Collections.binarySearch(lockObjects, prevNode) - 1); } catch (InterruptedException e) { e.printStackTrace(); } catch (KeeperException e) { e.printStackTrace(); } return false; } public boolean tryLock(long timeout, TimeUnit unit) { try { if (this.tryLock()) { return true; } return waitForLock(WAIT_LOCK, timeout); } catch (Exception e) { e.printStackTrace(); } return false; } // 等待锁 private boolean waitForLock(String prev, long waitTime) throws KeeperException, InterruptedException { Stat stat = zk.exists(ROOT_LOCK + "/" + prev, true); if (stat != null) { System.out.println(Thread.currentThread().getName() + "等待锁 " + ROOT_LOCK + "/" + prev); this.countDownLatch = new CountDownLatch(1); // 计数等待,若等到前一个节点消失,则precess中进行countDown,停止等待,获取锁 this.countDownLatch.await(waitTime, TimeUnit.MILLISECONDS); this.countDownLatch = null; System.out.println(Thread.currentThread().getName() + " 等到了锁"); } return true; } public void unlock() { try { System.out.println("释放锁 " + CURRENT_LOCK); zk.delete(CURRENT_LOCK, -1); CURRENT_LOCK = null; zk.close(); } catch (InterruptedException e) { e.printStackTrace(); } catch (KeeperException e) { e.printStackTrace(); } } public Condition newCondition() { return null; } public void lockInterruptibly() throws InterruptedException { this.lock(); } public class LockException extends RuntimeException { private static final long serialVersionUID = 1L; public LockException(String e){ super(e); } public LockException(Exception e){ super(e); } } }
测试代码
public class Test { static int n = 500; public static void secskill() { System.out.println(--n); } public static void main(String[] args) { Runnable runnable = new Runnable() { public void run() { DistributedLock lock = null; try { lock = new DistributedLock("127.0.0.1:2181", "test1"); lock.lock(); secskill(); System.out.println(Thread.currentThread().getName() + "正在运行"); } finally { if (lock != null) { lock.unlock(); } } } }; for (int i = 0; i < 10; i++) { Thread t = new Thread(runnable); t.start(); } } }
运行结果:
总体来说,如果了解到整个实现流程,使用zookeeper实现分布式锁并不是很困难,不过这也只是一个简单的实现,与前面实现Redis实现相比,本实现的稳定性更强,这是因为zookeeper的特性所致,在外界看来,zookeeper集群中每一个节点都是一致的。
完整代码可以在我的GitHub中查看:https://github.com/hongmoshui/DistributedLock
原文链接:https://www.cnblogs.com/liuyang0/p/6800538.html
原文地址:https://www.cnblogs.com/hongmoshui/p/10599190.html
时间: 2024-10-09 11:18:51