In a database system, a schedule is an ordering of the operations performed by a set of concurrent transactions. When multiple transactions are executed concurrently, the order in which their operations are executed can have a significant impact on the overall performance and correctness of the system.
For example, consider a bank database system that stores information about customer accounts and transactions. If multiple customers try to access their accounts and make transactions at the same time, the system must be able to handle these requests concurrently. A schedule for these concurrent transactions might look like:
yamlT1: Read account 1234T1: Withdraw $100 from account 1234T2: Read account 5678T2: Deposit $50 into account 5678T3: Read account 1234T3: Deposit $50 into account 1234T1: Write new account balance for account 1234T2: Write new account balance for account 5678T3: Write new account balance for account 1234In this example, transactions T1, T2, and T3 are executed concurrently. Transaction T1 reads from and updates the balance of account 1234, while transaction T2 reads from and updates the balance of account 5678. Transaction T3 reads from and updates the balance of account 1234. The schedule ensures that the transactions do not interfere with each other and that the final account balances are consistent with the transactions performed.
Concurrent execution of transactions improves overall system performance by allowing multiple transactions to be executed simultaneously, thus increasing the utilization of system resources such as CPU time and disk I/O. This can lead to better throughput and faster response times for users. However, concurrent execution can also introduce concurrency control issues, such as data inconsistencies and transaction conflicts, which must be managed by the system. Therefore, the system must use concurrency control mechanisms, such as locking or timestamp ordering, to ensure the correctness of the concurrent transactions.
