Introduction

In database management systems, concurrency control plays a crucial role in ensuring data integrity and efficient utilization of resources. One common problem that can occur in concurrent environments is a deadlock. A deadlock occurs when two or more transactions are waiting indefinitely for each other to release resources, resulting in a state where no progress can be made.

In this article, we will explore how deadlock handling is performed in the serializable isolation level.

Serializable Isolation Level

The serializable isolation level is the highest level of isolation provided by most database systems. It ensures that transactions are executed one at a time in a specific order, making their execution serial-like, hence the name.

To achieve serializability, a database system may implement various techniques, such as lock-based protocols or optimistic concurrency control (OCC). In this article, we will focus on deadlock handling within a lock-based protocol.

Deadlock Detection

In a serializable isolation level, the database system detects deadlocks by constantly monitoring the transaction dependency graph. The transaction dependency graph represents the dependencies between transactions based on the data items they access.

When a transaction requests a lock on a data item that is already locked by another transaction, a dependency edge is created in the transaction dependency graph. If this edge forms a cycle, a deadlock is detected.

Deadlock Resolution

Upon detecting a deadlock, the database system needs to resolve it. There are several approaches that can be taken:

1. Deadlock Detection and Rollback: The database system can choose to resolve the deadlock by rolling back one or more of the involved transactions. This approach releases the locked resources and allows the remaining transactions to continue execution.

2. Deadlock Prevention: In some cases, deadlocks can be prevented before they occur by carefully managing the locking order of resources. This approach ensures that transactions always request locks in a consistent order, preventing cyclic dependencies from forming.

3. Timeouts: Another approach is to set a timeout for each transaction. If a transaction exceeds its allocated time, it can be aborted and rolled back. This approach ensures that no transaction remains blocked indefinitely in a deadlock situation.

Conclusion

Deadlock handling in the serializable isolation level is an essential aspect of concurrency control in database systems. By continuously monitoring the transaction dependency graph, the database system can detect deadlocks and apply appropriate resolution strategies like rollback, prevention, or timeouts.

Understanding how deadlock handling works is crucial for database administrators and developers to ensure the smooth execution of transactions and maintain the integrity of data in concurrent environments.

#database #concurrency