Database clusters handle concurrent access and locking through various mechanisms to ensure data consistency and integrity. One common method is the use of locks, which can be either shared (read) or exclusive (write). When a transaction wants to read data, it acquires a shared lock, allowing other transactions to also read but not write to that data. When a transaction wants to write data, it acquires an exclusive lock, preventing other transactions from reading or writing to that data until the lock is released.
For example, in a multi-user environment, if two users try to update the same record simultaneously, the database cluster will manage this by granting an exclusive lock to one user's transaction, while the other user's transaction waits until the lock is released.
Another method used is optimistic locking, where version numbers or timestamps are used to detect conflicts. If a transaction tries to update data that has been modified since it was last read, the transaction will fail and need to be retried.
Database clusters also use techniques like sharding, where data is split across multiple servers, reducing contention by distributing the load. Replication can also help, by allowing reads to be distributed across replicas, offloading the primary server.
In the context of cloud services, platforms like Tencent Cloud offer managed database services that handle these complexities for you. For instance, Tencent Cloud's TDSQL (Tencent Distributed SQL Database) provides a distributed database solution with high availability and strong consistency, managing concurrent access and locking efficiently to support large-scale applications.