Update Locks: Used on resources that can be updated.
更新锁：用于可更新的资源。
Bulk Update Locks: Used when bulk-copying data into a table and the TABLOCK hint is specified.
大容量更新锁：在向表进行大容量数据复制且指定了TABLOCK提示时使用。
Update Locks: Used on resources that can be updated. It prevents a common form of deadlock that occurs when multiple sessions are reading, locking, and potentially updating resources later.
更新锁：用于可更新的资源。它可以防止当多个会话在读取，锁定以及随后可能进行的资源更新时发生的常见形式的死锁。
With this strategy, because you are not holding read locks on data, the chance of getting stale data exceptions when you execute the update operations increases.
通过此策略，由于您未对数据保持读取锁，因此在执行更新操作时遇到失效数据异常的机率会增加。
These locks are converted to exclusive locks while performing the actual update.
在执行实际更新时，这些锁定被转换为独占锁定。
There are no locks and synchronized blocks in the actor model, so the issues that arise from them — like deadlocks and the nefarious lost-update problem — aren't a problem.
角色模型中没有锁和同步块，所以不会出现由它们引发的问题，比如死锁、严重的丢失更新问题。
In the pessimistic locking scheme, explicit locks are taken against rows using the SQL SELECT FOR UPDATE statement. Data is then modified, and an SQL UPDATE is issued.
在悲观锁定方案中，通过使用SQLSELECTFORupdate语句对数据行进行显式锁定，然后更改数据，并执行SQL UPDATE。
Release the row locks so that other applications can SELECT, INSERT, UPDATE, and DELETE from the table (for example, use isolation level cursor stability or uncommitted read).
释放行锁，以便其他应用程序可以对表执行SELECT、INSERT、UPDATE和DELETE(例如，使用游标稳定性(curs or stability)隔离级别或未提交读(uncommitted read)隔离级别)。
Pessimistic concurrency locks data during update so that other users are not in danger of committing incompatible data changes.
保守式并发在更新期间锁定数据，使其他用户不会陷于提交不兼容数据更改的危险中。
Pessimistic concurrency locks data during update so that other users are not in danger of committing incompatible data changes.
保守式并发在更新期间锁定数据，使其他用户不会陷于提交不兼容数据更改的危险中。
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