Deadlock Handling

Deadlock is a situation in a database management system where two or more transactions are blocked waiting for each other to release resources, causing a circular wait. Deadlocks can cause significant performance issues and can even cause the system to stop responding.

There are several approaches to handling deadlocks, including prevention, detection, and resolution.

Deadlock prevention: One way to handle deadlocks is to prevent them from occurring in the first place. This can be done by using techniques such as lock ordering, time-outs, and resource allocation graphs. Lock ordering involves establishing a fixed order in which locks are requested and released to prevent circular waits. Time-outs involve setting a limit on the amount of time a transaction can hold a resource, forcing it to release the resource if the time limit is exceeded. Resource allocation graphs can be used to detect potential deadlocks before they occur.

Deadlock detection: Another way to handle deadlocks is to detect them as soon as they occur. This can be done by periodically checking the system for deadlock conditions using algorithms such as the banker’s algorithm or the wait-for graph algorithm. Once a deadlock is detected, the system can take action to resolve the deadlock.

Deadlock resolution: If a deadlock is detected, there are several ways to resolve it. One common approach is to use a timeout mechanism to force one of the transactions to abort, releasing the resources it is holding and allowing the other transaction(s) to proceed. Another approach is to use a rollback mechanism to undo the transactions involved in the deadlock, releasing the resources and allowing the system to continue.

In summary, handling deadlocks in a database management system involves preventing, detecting, and resolving deadlocks. Prevention techniques involve establishing a fixed order for locks, setting time-outs on resource usage, and using resource allocation graphs. Detection techniques involve periodically checking the system for deadlock conditions using algorithms such as the banker’s algorithm or the wait-for graph algorithm. Resolution techniques involve using timeout or rollback mechanisms to release resources and allow the system to continue.

Concurrency Control

Concurrency control is a technique used in computer science to manage access to shared resources in a concurrent environment. It ensures that multiple transactions accessing the same data do not interfere with each other, and that the integrity and consistency of the data are maintained.

Concurrency control is particularly important in multi-user database systems, where multiple users can simultaneously access the same data. In such systems, concurrency control mechanisms are used to ensure that data is accessed and modified in a controlled manner, and that data integrity and consistency are maintained.

There are several techniques for concurrency control, including locking, timestamp ordering, and optimistic concurrency control. Locking involves assigning locks to data items to prevent other transactions from accessing or modifying them. Timestamp ordering involves assigning timestamps to transactions and ordering them based on the timestamps to ensure that conflicting operations do not occur. Optimistic concurrency control assumes that conflicts are rare, and allows multiple transactions to operate on the same data simultaneously, but performs validation at the end to ensure that the data is consistent.

Concurrency control is an important aspect of database management systems and is essential for maintaining the consistency and integrity of data in multi-user environments.