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Redisson分布式锁源码解析

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Redisson锁继承Implements Reentrant Lock,所以具备 Reentrant Lock 锁中的一些特性:超时,重试,可中断等。加上Redisson中Redis具备分布式的特性,所以非常适合用来做Java中的分布式锁。 下面我们对其加锁、解锁过程中的源码细节进行一一分析。

锁的接口定义了一下方法:

分布式锁当中加锁,我们常用的加锁接口:

boolean tryLock(long waitTime, long leaseTime, TimeUnit unit) throws InterruptedException;

下面我们来看一下方法的具体实现:

public boolean tryLock(long waitTime, long leaseTime, TimeUnit unit) throws InterruptedException {
  long time = unit.toMillis(waitTime);
  long current = System.currentTimeMillis();
  final long threadId = Thread.currentThread().getId();
  Long ttl = tryAcquire(leaseTime, unit, threadId);
  // lock acquired
  if (ttl == null) {
   return true;
  }
  
  time -= (System.currentTimeMillis() - current);
  if (time <= 0) {
   acquireFailed(threadId);
   return false;
  }
  
  current = System.currentTimeMillis();
  final RFuture subscribeFuture = subscribe(threadId);
  if (!await(subscribeFuture, time, TimeUnit.MILLISECONDS)) {
   if (!subscribeFuture.cancel(false)) {
    subscribeFuture.addListener(new FutureListener() {
     @Override
     public void operationComplete(Future future) throws Exception {
      if (subscribeFuture.isSuccess()) {
       unsubscribe(subscribeFuture, threadId);
      }
     }
    });
   }
   acquireFailed(threadId);
   return false;
  }

  try {
   time -= (System.currentTimeMillis() - current);
   if (time <= 0) {
    acquireFailed(threadId);
    return false;
   }
  
   while (true) {
    long currentTime = System.currentTimeMillis();
    ttl = tryAcquire(leaseTime, unit, threadId);
    // lock acquired
    if (ttl == null) {
     return true;
    }

    time -= (System.currentTimeMillis() - currentTime);
    if (time = 0 && ttl < time) {
     getEntry(threadId).getLatch().tryAcquire(ttl, TimeUnit.MILLISECONDS);
    } else {
     getEntry(threadId).getLatch().tryAcquire(time, TimeUnit.MILLISECONDS);
    }

    time -= (System.currentTimeMillis() - currentTime);
    if (time <= 0) {
     acquireFailed(threadId);
     return false;
    }
   }
  } finally {
   unsubscribe(subscribeFuture, threadId);
  }
//  return get(tryLockAsync(waitTime, leaseTime, unit));
 }

首先我们看到调用tryAcquire尝试获取锁,在这里是否能获取到锁,是根据锁名称的过期时间TTL来判定的(TTL

下面我们接着看一下tryAcquire的实现:

private Long tryAcquire(long leaseTime, TimeUnit unit, long threadId) {
 return get(tryAcquireAsync(leaseTime, unit, threadId));
}

可以看到真正获取锁的操作经过一层get操作里面执行的,这里为何要这么操作,本人也不是太理解,如有理解错误,欢迎指正。

get 是由CommandAsyncExecutor(一个线程Executor)封装的一个Executor

设置一个单线程的同步控制器CountDownLatch,用于控制单个线程的中断信息。个人理解经过中间的这么一步:主要是为了支持线程可中断操作。

public V get(RFuture future) {
 if (!future.isDone()) {
  final CountDownLatch l = new CountDownLatch(1);
  future.addListener(new FutureListener() {
   @Override
   public void operationComplete(Future future) throws Exception {
    l.countDown();
   }
  });
  
  boolean interrupted = false;
  while (!future.isDone()) {
   try {
    l.await();
   } catch (InterruptedException e) {
    interrupted = true;
   }
  }
  
  if (interrupted) {
   Thread.currentThread().interrupt();
  }
 }

 // commented out due to blocking issues up to 200 ms per minute for each thread:由于每个线程的阻塞问题,每分钟高达200毫秒
 // future.awaitUninterruptibly();
 if (future.isSuccess()) {
  return future.getNow();
 }

 throw convertException(future);
}

我们进一步往下看:

private RFuture tryAcquireAsync(long leaseTime, TimeUnit unit, final long threadId) {
 if (leaseTime != -1) {
  return tryLockInnerAsync(leaseTime, unit, threadId, RedisCommands.EVAL_LONG);
 }
 RFuture ttlRemainingFuture = tryLockInnerAsync(commandExecutor.getConnectionManager().getCfg().getLockWatchdogTimeout(), TimeUnit.MILLISECONDS, threadId, RedisCommands.EVAL_LONG);
 ttlRemainingFuture.addListener(new FutureListener() {
  @Override
  public void operationComplete(Future future) throws Exception {
   if (!future.isSuccess()) {
    return;
   }

   Long ttlRemaining = future.getNow();
   // lock acquired
   if (ttlRemaining == null) {
    scheduleExpirationRenewal(threadId);
   }
  }
 });
 return ttlRemainingFuture;
}

首先判断锁是否有超时时间,有过期时间的话,会在后面获取锁的时候设置进去。没有过期时间的话,则会用默认的

private long lockWatchdogTimeout = 30 * 1000;

下面我们在进一步往下分析真正获取锁的操作:

RFuture tryLockInnerAsync(long leaseTime, TimeUnit unit, long threadId, RedisStrictCommand command) {
 internalLockLeaseTime = unit.toMillis(leaseTime);

 return commandExecutor.evalWriteAsync(getName(), LongCodec.INSTANCE, command,
    "if (redis.call('exists', KEYS[1]) == 0) then " +
     "redis.call('hset', KEYS[1], ARGV[2], 1); " +
     "redis.call('pexpire', KEYS[1], ARGV[1]); " +
     "return nil; " +
    "end; " +
    "if (redis.call('hexists', KEYS[1], ARGV[2]) == 1) then " +
     "redis.call('hincrby', KEYS[1], ARGV[2], 1); " +
     "redis.call('pexpire', KEYS[1], ARGV[1]); " +
     "return nil; " +
    "end; " +
    "return redis.call('pttl', KEYS[1]);",
    Collections.singletonList(getName()), internalLockLeaseTime, getLockName(threadId));
}

我把里面的重点信息做了以下三点总结:

1:真正执行的是一段具有原子性的Lua脚本,并且最终也是由CommandAsynExecutor去执行。

2:锁真正持久化到Redis时,用的hash类型key field value

3:获取锁的三个参数:getName()是逻辑锁名称,例如:分布式锁要锁住的methodName+params;internalLockLeaseTime是毫秒单位的锁过期时间;getLockName则是锁对应的线程级别的名称,因为支持相同线程可重入,不同线程不可重入,所以这里的锁的生成方式是:UUID+":"threadId。有的同学可能会问,这样不是很缜密:不同的JVM可能会生成相同的threadId,所以Redission这里加了一个区分度很高的UUID;

Lua脚本中的执行分为以下三步:

1:exists检查redis中是否存在锁名称;如果不存在,则获取成功;同时把逻辑锁名称KEYS[1],线程级别的锁名称[ARGV[2],value=1,设置到redis。并设置逻辑锁名称的过期时间ARGV[2],返回;

2:如果检查到存在KEYS[1],[ARGV[2],则说明获取成功,此时会自增对应的value值,记录重入次数;并更新锁的过期时间

3:key不存,直接返回key的剩余过期时间(-2)

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