Last modified: June 28, 2018
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Deadlocks are a critical issue in database systems that occur when two or more transactions are waiting indefinitely for each other to release locks on resources. This situation leads to a standstill where none of the involved transactions can proceed, potentially halting system operations and affecting performance.
Imagine a scenario where two transactions are each holding a lock on a resource the other needs. Neither can proceed until the other releases its lock, resulting in a deadlock.
Deadlock Scenario:
Transaction T1:
Holds Lock on Resource A
Requests Lock on Resource B (held by T2)
Transaction T2:
Holds Lock on Resource B
Requests Lock on Resource A (held by T1)
Result: Both transactions are waiting indefinitely.
In this illustration, Transaction T1 has locked Resource A and is waiting for Resource B, while Transaction T2 has locked Resource B and is waiting for Resource A. Since neither transaction can release its lock until it obtains the other resource, they are stuck in a deadlock.
After reading the material, you should be able to answer the following questions:
Deadlocks arise from the way transactions acquire and hold locks on resources. They are particularly problematic in environments with high concurrency, where multiple transactions frequently access shared resources.
Consider the following real-world analogy: two drivers meet on a narrow bridge, each unwilling to reverse. Both are waiting for the other to move, and traffic comes to a standstill. Similarly, in a database, transactions can become deadlocked when they wait for each other to release resources.
Several factors contribute to the occurrence of deadlocks in database systems, highlighting the importance of effective transaction and lock management:
Database systems use various methods to detect deadlocks and resolve them promptly.
One common technique involves constructing a wait-for graph, which represents transactions as nodes and waiting relationships as edges. A cycle in this graph indicates a deadlock.
Wait-For Graph Example:
T1 --> T2 --> T3 --> T1
Cycle Detected: T1 is waiting for T2, T2 for T3, and T3 for T1.
In this graph, transactions are waiting in a circular chain, confirming the presence of a deadlock.
Some database management systems (DBMS) automatically monitor for deadlocks by tracking lock requests and holdings. When a deadlock is detected, the system can take corrective action, such as terminating one of the involved transactions.
Preventing deadlocks involves designing transactions and systems to avoid the conditions that lead to them.
By acquiring locks in a consistent, predefined order, transactions reduce the risk of circular wait conditions.
Example:
All transactions acquire locks in the order: Resource A, then Resource B.
Transaction T1:
Locks Resource A
Locks Resource B
Transaction T2:
Waits for Resource A (since T1 holds it)
Locks Resource A
Locks Resource B
In this approach, T2 cannot lock Resource B before locking Resource A, preventing a circular wait.
Implementing timeouts for lock requests ensures that transactions do not wait indefinitely.
Establishing a hierarchy for resources and enforcing that transactions can only lock higher-level resources after lower-level ones prevents deadlocks.
When prevention fails, and a deadlock occurs, the system must resolve it to maintain functionality.
The DBMS can terminate one of the deadlocked transactions, rolling back its operations to free up resources.
In some cases, database administrators may need to manually identify and resolve deadlocks, especially if they occur frequently or impact critical operations.
Let's look at a SQL example to illustrate how deadlocks can happen and be addressed.
Transaction T1:
BEGIN TRANSACTION;
UPDATE Accounts SET Balance = Balance - 100 WHERE AccountID = 1;
-- Locks row with AccountID = 1
WAITFOR DELAY '00:00:05'; -- Simulate processing time
UPDATE Accounts SET Balance = Balance + 100 WHERE AccountID = 2;
-- Requests lock on row with AccountID = 2
COMMIT;
Transaction T2:
BEGIN TRANSACTION;
UPDATE Accounts SET Balance = Balance - 50 WHERE AccountID = 2;
-- Locks row with AccountID = 2
WAITFOR DELAY '00:00:05'; -- Simulate processing time
UPDATE Accounts SET Balance = Balance + 50 WHERE AccountID = 1;
-- Requests lock on row with AccountID = 1
COMMIT;
Interpretation:
Resolution:
To minimize the risk of deadlocks, it is essential to follow best practices that promote efficient resource utilization and transaction management:
Deadlocks aren't limited to database transactions; they can also occur in multithreaded applications when threads contend for shared resources.
Thread Deadlock Example:
Thread A:
Locks Mutex M1
Waits for Mutex M2
Thread B:
Locks Mutex M2
Waits for Mutex M1
Applying similar strategies of lock ordering and timeouts can help prevent deadlocks in these environments.
Understanding the difference between deadlocks and livelocks is crucial for effectively managing transaction conflicts:
Beyond direct locking mechanisms, other factors play a role in preventing deadlocks and improving system efficiency:
To deepen your understanding of deadlocks and concurrency control, consider exploring: