Distributed Databases Questions Long
Distributed concurrency control refers to the management of concurrent access to data in a distributed database system. It ensures that multiple transactions executing concurrently in different nodes of the distributed system do not interfere with each other and maintain the consistency and integrity of the database.
Achieving distributed concurrency control involves various techniques and protocols. Some of the commonly used methods are:
1. Locking-based protocols: In this approach, locks are used to control access to data items. Each transaction requests and acquires locks on the data items it needs to access. Locks can be of different types such as shared locks (read-only access) and exclusive locks (write access). The locks are released once the transaction completes its operation on the data item. Locking-based protocols ensure serializability by preventing conflicting operations on the same data item.
2. Timestamp-based protocols: In this approach, each transaction is assigned a unique timestamp that represents its order of execution. Transactions are scheduled based on their timestamps, and conflicts are resolved by comparing the timestamps. If a transaction with a higher timestamp tries to access a data item locked by a transaction with a lower timestamp, it is either delayed or aborted. Timestamp-based protocols ensure serializability by enforcing a total order of transactions.
3. Optimistic concurrency control: This approach assumes that conflicts between transactions are rare. Transactions are allowed to execute concurrently without acquiring locks. However, before committing, each transaction validates its changes against the changes made by other concurrent transactions. If conflicts are detected, the transaction is rolled back and re-executed. Optimistic concurrency control reduces the overhead of acquiring and releasing locks but requires additional validation steps.
4. Two-phase locking: This protocol is an extension of the locking-based approach. It ensures serializability by enforcing two phases: the growing phase and the shrinking phase. In the growing phase, a transaction can acquire locks but cannot release any locks. In the shrinking phase, a transaction can release locks but cannot acquire any new locks. Two-phase locking prevents conflicts by ensuring that no transaction can acquire a lock after releasing a lock.
5. Multiversion concurrency control: This approach allows multiple versions of a data item to coexist in the database. Each transaction reads a consistent snapshot of the database, considering the appropriate version of each data item. When a transaction updates a data item, a new version is created, and the transaction writes to the new version. Multiversion concurrency control allows for high concurrency as transactions can read and write different versions of data items simultaneously.
These are some of the techniques used to achieve distributed concurrency control in distributed databases. The choice of the technique depends on factors such as the level of concurrency, the frequency of conflicts, and the performance requirements of the system.