How can I handle concurrency issues in SQL?

How can I handle concurrency issues in SQL?

Concurrency issues in SQL occur when multiple transactions are executed simultaneously, potentially leading to data inconsistencies. You can handle these issues using techniques like locking, isolation levels, and optimistic concurrency control.

What are the different isolation levels in SQL?

The main isolation levels in SQL are Read Uncommitted, Read Committed, Repeatable Read, and Serializable. Each level balances performance and consistency differently.

Can you explain optimistic concurrency control?

Optimistic concurrency control allows multiple transactions to proceed without locking resources. It checks for conflicts before committing changes, rolling back if a conflict is detected.

What are the pros and cons of using locks?

Locks can prevent data corruption but may lead to performance bottlenecks and deadlocks if not managed properly. It's essential to choose the right locking strategy.

How do I implement a retry mechanism for failed transactions?

You can implement a retry mechanism by catching exceptions during transaction commits and retrying the operation after a brief wait, ensuring to limit the number of retries to avoid infinite loops.