Deadlock Detection & Resolution in SQL

1. Introduction

In relational databases, transactions are executed concurrently to optimize performance. However, this can lead to deadlocks, where two or more transactions are waiting for each other to release locks, causing all of them to be stalled.

2. Key Concepts

• **Transaction**: A sequence of operations performed as a single logical unit of work.
• **Locking**: Mechanism to control access to data by multiple transactions.
• **Deadlock**: A situation where two or more transactions are unable to proceed because each is waiting for the other to release a lock.
• **Wait-for Graph**: A directed graph that represents the waits among transactions.

3. Deadlock Detection

Deadlock detection involves identifying cycles in the wait-for graph. If a cycle exists, it indicates a deadlock.

        -- Pseudo code for Deadlock Detection
        function detectDeadlock(transactions):
            waitForGraph = buildWaitForGraph(transactions)
            return hasCycle(waitForGraph)
        

4. Deadlock Resolution

Once a deadlock is detected, it can be resolved through various strategies:

1. Transaction Termination: Abort one or more transactions to break the deadlock.
2. Timeouts: Allow transactions to wait for a specific period and then abort.
3. Wait-Die and Wound-Wait Schemes: Prioritize transactions based on timestamps.

        -- Pseudo code for Deadlock Resolution
        function resolveDeadlock(transactions):
            deadlocked = detectDeadlock(transactions)
            if deadlocked:
                abortTransaction(findVictim(transactions))
        

5. Best Practices

To minimize the likelihood of deadlocks:

• Access resources in a consistent order across transactions.
• Keep transactions short and efficient.
• Use lower isolation levels if appropriate.
• Regularly monitor and analyze database performance.

6. FAQ