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A locking mechanism is a fundamental technique used in database management systems (DBMS) to manage concurrent access to data. It ensures that multiple transactions can occur simultaneously without leading to data inconsistency or corruption. There are two primary types of locks: Shared Lock (S Lock) and Exclusive Lock (X Lock). A Shared Lock allows multiple transactions to read a resource but not modify it. If a transaction holds a shared lock, other transactions can also acquire shared locks on the same resource, but no transaction can acquire an exclusive lock on it. An Exclusive Lock, on the other hand, allows a transaction to both read and modify a resource. If a transaction holds an exclusive lock, no other transaction can acquire any type of lock (shared or exclusive) on the same resource.

Locks play a crucial role in concurrency control by preventing conflicts and maintaining consistency. They ensure that only one transaction can modify a resource at a time, thus avoiding the "lost update" problem where two transactions simultaneously update the same data, leading to one update being lost. By controlling access to data, locks help maintain database consistency; for example, if a transaction is reading data, another transaction cannot modify that data until the read is complete. While locks are essential for these reasons, they also necessitate mechanisms for deadlock handling, as deadlocks can occur when transactions wait indefinitely for each other to release locks.

Timestamp ordering is a concurrency control mechanism used in database management systems to ensure that transactions are executed in a serializable manner, meaning the outcome is the same as if the transactions were executed one after the other, without overlapping in time. This method assigns a unique timestamp to each transaction when it begins, which helps in managing the order of operations and resolving conflicts. Each transaction is given a unique timestamp when it starts. This timestamp can be based on the system clock or a logical counter. There are two main types of timestamps: Start Timestamp(The time when the transaction T starts), and Commit Time Stamp (The time when the transaction T commits). When a transaction T wants to read a data item, the system checks the write timestamp of the data item. If the write timestamp of the data item is greater than the transaction's timestamp, it means a newer transaction has already written to the data item, and the read operation is not allowed to maintain serializability.