但不能在数据库中无限地保持写锁。
But a write lock in the database can't be held indefinitely.
然后该写锁阻塞了其他事务。
FD列中的大写W表示该应用程序具有对整个文件的写锁。
The capital W in the FD column indicates that the application has a write lock on the whole file.
例如，如果你有六个数据库，其中一个有写锁，其他的五个仍然可以进行读写。
For example, if you have six databases and one takes a write lock, the other five are still available for read and write.
他们并不会阻止不同的事务在相同的间隙获取锁，因此间隙读锁和间隙写锁有相同的影响。
They do not prevent different transactions from taking gap locks on the same gap. Thus, a gap X-lock has the same effect as a gap S-lock.
之所以将这种技术称之为 “开销较低的读-写锁” 是因为您使用了不同的同步机制进行读写操作。
The reason this technique is called the "cheap read-write lock" is that you are using different synchronization mechanisms for reads and writes.
显然，如果您使用的是原版的读/写锁，那么按照标准自旋锁的用法使用这个自旋锁，而不区分读线程和写线程。
Obviously, if your use of the lock is reader/writer in nature, this spinlock should be used over the standard spinlock, which doesn't differentiate between readers and writers.
索引器接收到IASTTranslationUnit后，会得到在PDOM上的一个写锁并开始保持TranslationUnit的数据。
After the indexer receives the IASTTranslationUnit, it gets a write lock on the PDOM and begins persisting the TranslationUnit's data.
如果不按这种方式使用 pthread_setschedprio 设置写线程的优先级，根据读写锁的性质，很容易看出写线程可能会饿死。
If you don't adhere to this approach in prioritizing writer threads using pthread_setschedprio, then given the nature of read-write lock, it is easy to see how writer threads could starve.
有了这一类型的锁，并发应用程序就可以读或写已锁定的表。
With this type of lock, concurrent applications can read from or write to the locked table.
存放数据的时候，他先要获得互斥锁，再往总线上写数据，最后再释放互斥锁。
When publishing its data, it would acquire a mutex, do writes to the bus, and release the mutex.
因为添加和取出数据操作使用相同的互斥锁，所以读取数据的速度会影响写数据的线程访问锁。
Because you're sharing the same mutex for push and pop operations, the data-read speed is somewhat compromised as writer threads access the lock.
写操作完成之后，它刷新文件缓冲区并解除文件锁。
On completion of the writing, it flushes the file buffers and unlocks the file.
s锁允许使用只读查询的并发应用程序访问目标表，但是防止应用程序写数据到表中。
The s lock allows concurrent applications that use read-only queries to access the target table, but applications attempting to write data to the table are prevented from doing so.
造成延迟的惟一原因是写线程太多，要等待很长时间才能获得锁。
The only reason for the delay could be that there are too many writer threads, and sufficient time has elapsed before a lock could be acquired.
现在，DB 2 9.7使用的默认锁状态允许读者不等待写操作的结果。
DB2 9.7 now USES the default-locking state so that readers will not wait for the outcome of a pending write.
新增的“currentlycommitted”锁语法可以消除读和写工作负载之间的冲突，让数据库实现真正的时间点响应。
A newly added "currently committed" locking syntax eliminates the conflict between read and write workloads so the database can deliver a true point-in-time response.
因为本例中的写操作违反了使用volatile的第一个条件，因此不能使用volatile安全地实现计数器——您必须使用锁。
Because the writes in this case violate the first condition for using volatile, you cannot use volatile to safely implement the counter — you must use locking.
然而，如果读操作远远超过写操作，您可以结合使用内部锁和volatile变量来减少公共代码路径的开销。
However, if reads greatly outnumber modifications, you can combine intrinsic locking and volatile variables to reduce the cost on the common code path.
这是因为JFS2在实现时使用了写独占(write - exclusive)索引节点锁，允许多个用户同时读取相同的文件。
This is due to the way in which JFS2 is implemented with a write-exclusive inode lock, allowing multiples users to read the same file simultaneously.
在某些情况下，如果读操作远远大于写操作，volatile变量还可以提供优于锁的性能优势。
In situations where reads greatly outnumber writes, volatile variables may also provide a performance advantage over locking.
每个bucket都有一个锁，而且该锁在遍历bucket(为了读或写)的时候被获取。
For each bucket, there's a lock, and that lock is acquired when traversing a bucket either for read or write.
数据同步方面系统采用了域一致性模型、多写协议，和基于锁的同步方式；
The system of this thesis employs scope consistency model, multi-write and lock-based cache protocol. In communication module, we propose a new framework.
一个写线程释放一个锁之后，另一个读线程随后获取了同一个锁。本质上，线程释放锁时会将强制刷新工作内存中的脏数据到主内存中，获取一个锁将强制线程装载(或重新装载)字段的值。
In essence, releasing a lock forces a flush of all writes from working memory employed by the thread, and acquiring a lock forces a (re) load of the values of accessible fields.
分布式锁管理机制实现了GOS之间数据访问的同步协调，写通和写—无效的数据更新策略保证了GOS的缓存一致性。
The distributed lock system is used to synchronize GOS steps when accessing data. The consistency of the distributed cache is guaranteed by updating strategies of write-through and write-invalidate.
分布式锁管理机制实现了GOS之间数据访问的同步协调，写通和写—无效的数据更新策略保证了GOS的缓存一致性。
The distributed lock system is used to synchronize GOS steps when accessing data. The consistency of the distributed cache is guaranteed by updating strategies of write-through and write-invalidate.
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