Deadlock in Database Management System

Abhishek Pratap Singh
3 min readFeb 2, 2023

A deadlock is a situation in database management systems (DBMS) where two or more transactions are blocked, waiting for the release of locks held by the other transactions. This creates a cycle of waiting, where each transaction is waiting for a lock held by another transaction, and no progress can be made.

Deadlocks can occur in DBMS when multiple transactions access the same data simultaneously and each transaction holds locks on some data that the other transactions need. This can lead to a situation where each transaction is waiting for a lock held by the other, and neither can proceed.

Deadlocks can have a significant impact on the performance and stability of a database system, as they can cause transactions to hang and result in lost updates or data corruption. To prevent deadlocks, DBMS typically implement deadlock detection and resolution algorithms that monitor the lock state of transactions and resolve deadlocks by releasing locks or rolling back transactions.

Example:

Consider a scenario where two transactions, T1 and T2, are accessing the same database. T1 holds a lock on resource A and is waiting for a lock on resource B, while T2 holds a lock on resource B and is waiting for a lock on resource A. This creates a deadlock situation, as each transaction is waiting for the other to release a lock.

Ways to Resolve or Manage Deadlocks in Database Management Systems

There are several ways to resolve or manage deadlocks in database management systems:

  1. Timeout: Set a timeout for transactions, so that if a transaction is waiting for a lock for too long, it will be automatically rolled back.
  2. Rollback: Roll back one of the transactions involved in the deadlock, releasing its locks and allowing the other transaction to proceed. This approach sacrifices the data changes made by the rolled back transaction to resolve the deadlock.
  3. Prioritization: Prioritize transactions based on their importance, and resolve deadlocks by rolling back lower-priority transactions.
  4. Ordering: Enforce a strict ordering of locks, so that deadlocks cannot occur.
  5. Deadlock Detection and Resolution: Implement a deadlock detection algorithm that regularly monitors the lock state of transactions and automatically resolves deadlocks by releasing locks or rolling back transactions.
  6. Deadlock Prevention: Implement techniques to prevent deadlocks from occurring in the first place, such as avoiding cycles of waiting, limiting the number of locks held by transactions, and enforcing a strict ordering of locks.

The choice of deadlock management strategy will depend on the specific requirements of the database application and the trade-off between concurrency and consistency. It is important to implement a comprehensive deadlock management strategy to ensure the stability and performance of the database system.

Conclusion:

Deadlocks in database management systems can cause significant performance and stability issues, as they can block transactions and result in lost updates or data corruption. To prevent deadlocks, DBMS implement deadlock detection and resolution algorithms that monitor the lock state of transactions and resolve deadlocks by releasing locks or rolling back transactions. It is important to design database applications and transactions in a way that minimizes the risk of deadlocks, by avoiding the creation of cycles of waiting. Additionally, regularly monitoring the lock state of transactions can help detect and resolve deadlocks before they cause significant harm.

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Abhishek Pratap Singh

Software Engineer || Co- Founder || B-Plan contest finalist at IIT Kharagpur || 1st Rank on SQL- HackerRank