分布式锁实现（二）：Zookeeper
前言
紧跟上文的：分布式锁实现（一）：Redis ，这篇我们用Zookeeper来设计和实现分布式锁，并且研究下开源客户端工具Curator的分布式锁源码
设计实现
一、基本算法
1.在某父节点下创建临时有序节点
2.判断创建的节点是否是当前父节点下所有子节点中序号最小的
3.是序号最小的成功获取锁，否则监听比自己小的那个节点，进行watch，当该节点被删除的时候通知当前节点，重新获取锁
4.解锁的时候删除当前节点
二、关键点
临时有序节点
实现Zookeeper分布式锁关键就在于其[临时有序节点]的特性，在Zookeeper中有四种节点
1.PERSISTENT 持久，若不手动删除就永久存在
2.PERSISTENT_SEQUENTIAL 持久有序节点，zookeeper会为节点编号（保证有序）
3.EPHEMERAL 临时，一个客户端会话断开后会自动删除
4.EPHEMERAL_SEQUENTIAL 临时有序节点，zookeeper会为节点编号（保证有序）
监听
Zookeeper提供事件监听机制，通过对节点、节点数据、子节点都提供了监听，我们通过这种监听watcher机制实现锁的等待
三、代码实现
我们基于ZkClient这个客户端来实现，当然也可以用原生Zookeeper API,大致是一样的
坐标如下：
<dependency>
<groupId>com.101tec</groupId>
<artifactId>zkclient</artifactId>
<version>0.2</version>
</dependency>
代码如下：
public class MyDistributedLock {
private ZkClient zkClient;
private String name;
private String currentLockPath;
private CountDownLatch countDownLatch;
private static final String PARENT_LOCK_PATH = "/distribute_lock";
public MyDistributedLock(ZkClient zkClient, String name) {
this.zkClient = zkClient;
this.name = name;
}
//加锁
public void lock() {
//判断父节点是否存在，不存在就创建
if (!zkClient.exists(PARENT_LOCK_PATH)) {
try {
//多个线程只会成功建立一次
zkClient.createPersistent(PARENT_LOCK_PATH);
} catch (Exception ignored) {
}
}
//创建当前目录下的临时有序节点
currentLockPath = zkClient.createEphemeralSequential(PARENT_LOCK_PATH + "/", System.currentTimeMillis());
//校验是否最小节点
checkMinNode(currentLockPath);
}
//解锁
public void unlock() {
System.out.println("delete : " + currentLockPath);
zkClient.delete(currentLockPath);
}
private boolean checkMinNode(String lockPath) {
//获取当前目录下所有子节点
List<String> children = zkClient.getChildren(PARENT_LOCK_PATH);
Collections.sort(children);
int index = children.indexOf(lockPath.substring(PARENT_LOCK_PATH.length() + 1));
if (index == 0) {
System.out.println(name + "：success");
if (countDownLatch != null) {
countDownLatch.countDown();
}
return true;
} else {
String waitPath = PARENT_LOCK_PATH + "/" + children.get(index - 1);
//等待前一个节点释放的监听
waitForLock(waitPath);
return false;
}
}
private void waitForLock(String prev) {
System.out.println(name + " current path :" + currentLockPath + "：fail add listener" + " wait path :" + prev);
countDownLatch = new CountDownLatch(1);
zkClient.subscribeDataChanges(prev, new IZkDataListener() {
@Override
public void handleDataChange(String s, Object o) throws Exception {
}
@Override
public void handleDataDeleted(String s) throws Exception {
System.out.println("prev node is done");
checkMinNode(currentLockPath);
}
});
if (!zkClient.exists(prev)) {
return;
}
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
countDownLatch = null;
}
}
加锁
-
zkClient.exists先判断父节点是否存在，不存在就创建，zookeeper可以保证只会创建成功一次
-
在当前目录下zkClient.createEphemeralSequential创建临时有序节点，再判断当前目录下此节点是否为序号最小的，如果是，成功获取锁，否则的话拿比自己小的节点，并做监听
-
waitForLock等待比自己小的节点，subscribeDataChanges监听一个节点的变化，handleDataDeleted里面再次做checkMinNode的判断
-
监听完毕后，再判断一次此节点是否存在，因为在监听的过程中有可能之前小的那个节点重新释放了锁，如果之前节点不存在的话，无需在这里等待，这里的等待是通过countDownLatch实现的
解锁
解锁就是通过zkClient的delete删除当前节点
测试用例
通过启动多个线程来测试lock、unlock的过程，查看是否有序
public class MyDistributedLockTest {
public static void main(String[] args) {
ZkClient zk = new ZkClient("127.0.0.1:2181", 5 * 10000);
for (int i = 0; i < 20; i++) {
String name = "thread" + i;
Thread thread = new Thread(() -> {
MyDistributedLock myDistributedLock = new MyDistributedLock(zk, name);
myDistributedLock.lock();
// try {
// Thread.sleep(1 * 1000);
// } catch (InterruptedException e) {
// e.printStackTrace();
// }
myDistributedLock.unlock();
});
thread.start();
}
}
}
执行结果如下，多线程情况下lock/unlock和监听一切正常：
thread1 current path :/distribute_lock2/0000000007：fail add listener wait path :/distribute_lock2/0000000006
thread6 current path :/distribute_lock2/0000000006：fail add listener wait path :/distribute_lock2/0000000005
thread3：success
delete : /distribute_lock2/0000000000
thread2 current path :/distribute_lock2/0000000005：fail add listener wait path :/distribute_lock2/0000000004
thread7 current path :/distribute_lock2/0000000004：fail add listener wait path :/distribute_lock2/0000000003
thread9 current path :/distribute_lock2/0000000009：fail add listener wait path :/distribute_lock2/0000000008
thread5 current path :/distribute_lock2/0000000008：fail add listener wait path :/distribute_lock2/0000000007
thread0 current path :/distribute_lock2/0000000001：fail add listener wait path :/distribute_lock2/0000000000
thread8 current path :/distribute_lock2/0000000002：fail add listener wait path :/distribute_lock2/0000000001
thread4 current path :/distribute_lock2/0000000003：fail add listener wait path :/distribute_lock2/0000000002
delete : /distribute_lock2/0000000001
prev node is done
thread8：success
delete : /distribute_lock2/0000000002
prev node is done
thread4：success
delete : /distribute_lock2/0000000003
prev node is done
thread7：success
delete : /distribute_lock2/0000000004
prev node is done
thread2：success
delete : /distribute_lock2/0000000005
prev node is done
thread6：success
delete : /distribute_lock2/0000000006
prev node is done
thread1：success
delete : /distribute_lock2/0000000007
prev node is done
thread5：success
delete : /distribute_lock2/0000000008
prev node is done
thread9：success
delete : /distribute_lock2/0000000009
Curator源码分析
一、基本使用
RetryPolicy retryPolicy = new ExponentialBackoffRetry(1000, 3);
CuratorFramework client = CuratorFrameworkFactory.newClient("127.0.0.1:2181", retryPolicy);
client.start();
InterProcessMutex lock2 = new InterProcessMutex(client, "/test");
try {
lock.acquire();
//业务
} catch (Exception e) {
e.printStackTrace();
} finally {
lock.release();
}
-
CuratorFrameworkFactory.newClient获取zookeeper的客户端，retryPolicy指定重试策略，开启客户端
-
Curator本身提供了多种锁的实现，这里我们以InterProcessMutex可重入锁为例， lock.acquire()方法获取锁，lock.release()来释放锁，acquire方法也提供了重载的等待时间参数
二、源码分析
加锁
acquire内部就直接internalLock方法，传了-1的等待时间
public void acquire() throws Exception {
if(!this.internalLock(-1L, (TimeUnit)null)) {
throw new IOException("Lost connection while trying to acquire lock: " + this.basePath);
}
}
internalLock方法首先判断是否是重入锁，通过ConcurrentMap维护线程和一个原子计数器，非重入锁的话，再通过attemptLock去获取锁
private boolean internalLock(long time, TimeUnit unit) throws Exception
{
/*
Note on concurrency: a given lockData instance
can be only acted on by a single thread so locking isn't necessary
*/
Thread currentThread = Thread.currentThread();
LockData lockData = threadData.get(currentThread);
if ( lockData != null )
{
// re-entering
lockData.lockCount.incrementAndGet();
return true;
}
String lockPath = internals.attemptLock(time, unit, getLockNodeBytes());
if ( lockPath != null )
{
LockData newLockData = new LockData(currentThread, lockPath);
threadData.put(currentThread, newLockData);
return true;
}
return false;
}
attemptLock在这里进行循环等待，createsTheLock方法去创建节点，internalLockLoop去判断当前节点是否是最小节点
String attemptLock(long time, TimeUnit unit, byte[] lockNodeBytes) throws Exception
{
final long startMillis = System.currentTimeMillis();
final Long millisToWait = (unit != null) ? unit.toMillis(time) : null;
final byte[] localLockNodeBytes = (revocable.get() != null) ? new byte[0] : lockNodeBytes;
int retryCount = 0;
String ourPath = null;
boolean hasTheLock = false;
boolean isDone = false;
while ( !isDone )
{
isDone = true;
try
{
ourPath = driver.createsTheLock(client, path, localLockNodeBytes);
hasTheLock = internalLockLoop(startMillis, millisToWait, ourPath);
}
catch ( KeeperException.NoNodeException e )
{
// gets thrown by StandardLockInternalsDriver when it can't find the lock node
// this can happen when the session expires, etc. So, if the retry allows, just try it all again
if ( client.getZookeeperClient().getRetryPolicy().allowRetry(retryCount++, System.currentTimeMillis() - startMillis, RetryLoop.getDefaultRetrySleeper()) )
{
isDone = false;
}
else
{
throw e;
}
}
}
if ( hasTheLock )
{
return ourPath;
}
return null;
}
createsTheLock就是调用curator封装的api去创建临时有序节点
public String createsTheLock(CuratorFramework client, String path, byte[] lockNodeBytes) throws Exception
{
String ourPath;
if ( lockNodeBytes != null )
{
ourPath = client.create().creatingParentContainersIfNeeded().withProtection().withMode(CreateMode.EPHEMERAL_SEQUENTIAL).forPath(path, lockNodeBytes);
}
else
{
ourPath = client.create().creatingParentContainersIfNeeded().withProtection().withMode(CreateMode.EPHEMERAL_SEQUENTIAL).forPath(path);
}
return ourPath;
}
internalLockLoop锁判断，内部就是driver.getsTheLock去判断是否是当前目录下最小节点，如果是的话，返回获取锁成功，否则的话对previousSequencePath进行监听，监听动作完成后再对等待时间进行重新判断
private boolean internalLockLoop(long startMillis, Long millisToWait, String ourPath) throws Exception
{
boolean haveTheLock = false;
boolean doDelete = false;
try
{
if ( revocable.get() != null )
{
client.getData().usingWatcher(revocableWatcher).forPath(ourPath);
}
while ( (client.getState() == CuratorFrameworkState.STARTED) && !haveTheLock )
{
List<String> children = getSortedChildren();
String sequenceNodeName = ourPath.substring(basePath.length() + 1); // +1 to include the slash
PredicateResults predicateResults = driver.getsTheLock(client, children, sequenceNodeName, maxLeases);
if ( predicateResults.getsTheLock() )
{
haveTheLock = true;
}
else
{
String previousSequencePath = basePath + "/" + predicateResults.getPathToWatch();
synchronized(this)
{
try
{
// use getData() instead of exists() to avoid leaving unneeded watchers which is a type of resource leak
client.getData().usingWatcher(watcher).forPath(previousSequencePath);
if ( millisToWait != null )
{
millisToWait -= (System.currentTimeMillis() - startMillis);
startMillis = System.currentTimeMillis();
if ( millisToWait <= 0 )
{
doDelete = true; // timed out - delete our node
break;
}
wait(millisToWait);
}
else
{
wait();
}
}
catch ( KeeperException.NoNodeException e )
{
// it has been deleted (i.e. lock released). Try to acquire again
}
}
}
}
}
catch ( Exception e )
{
ThreadUtils.checkInterrupted(e);
doDelete = true;
throw e;
}
finally
{
if ( doDelete )
{
deleteOurPath(ourPath);
}
}
return haveTheLock;
}
解锁
release代码相对来说比较简单，就是先判断map里面是否存在当前线程的锁计数，不存在抛出异常，存在的话，进行原子减一操作，releaseLock内部就是删除节点操作，小于0的时候，从map里面移除
public void release() throws Exception
{
/*
Note on concurrency: a given lockData instance
can be only acted on by a single thread so locking isn't necessary
*/
Thread currentThread = Thread.currentThread();
LockData lockData = threadData.get(currentThread);
if ( lockData == null )
{
throw new IllegalMonitorStateException("You do not own the lock: " + basePath);
}
int newLockCount = lockData.lockCount.decrementAndGet();
if ( newLockCount > 0 )
{
return;
}
if ( newLockCount < 0 )
{
throw new IllegalMonitorStateException("Lock count has gone negative for lock: " + basePath);
}
try
{
internals.releaseLock(lockData.lockPath);
}
finally
{
threadData.remove(currentThread);
}
}
后记
分布式锁的实现目前主流比较常用的实现就是Redis和Zookeeper了，相比较自己的实现，Redission和Curator的设计实现更为优秀，也更值得我们借鉴和学习
千里之行，积于跬步;万里之船，成于罗盘，共勉。
千里之行，积于跬步;万里之船，成于罗盘，共勉。
