DBMS Concurrency Control | Database Management System (DBMS) - Software Development PDF Download

Introduction

In the world of databases, concurrency control plays a vital role in ensuring data consistency and integrity when multiple users or processes concurrently access and modify the same data. Without proper concurrency control mechanisms, conflicts and anomalies can occur, leading to incorrect results and data corruption. In this article, we will explore the basics of concurrency control in DBMS, along with simple examples and code snippets to help you understand the concepts better.

What is Concurrency Control?

Concurrency control is a mechanism used in database management systems (DBMS) to ensure that multiple users or processes can access and manipulate shared data concurrently without causing inconsistencies or conflicts. It helps maintain data integrity by coordinating and synchronizing the execution of concurrent transactions.

Types of Concurrency Control

There are several approaches to concurrency control in DBMS. Let's explore two common techniques:

(a) Lock-Based Concurrency Control: In lock-based concurrency control, transactions acquire locks on data items to prevent other transactions from accessing or modifying them concurrently. Locks can be of two types: shared locks and exclusive locks.

• Shared Lock: Allows multiple transactions to read (but not modify) the same data concurrently.
• Exclusive Lock: Prevents other transactions from accessing or modifying data until the lock is released.

(b) Timestamp-Based Concurrency Control: Timestamp-based concurrency control assigns a unique timestamp to each transaction to determine the order in which they are allowed to execute. The timestamps can be used to detect conflicts and determine the appropriate action to take.

Example 1: Lock-Based Concurrency Control

Let's consider a simple scenario with two transactions, T1 and T2, trying to update a shared resource, such as a bank account balance, simultaneously.

# Python code for lock-based concurrency control

# Initial balance

balance = 100

# Transaction 1 (T1)

def transaction_1():

    global balance

    # Acquire exclusive lock

    # ...

    balance += 50

    # Release the lock

    # ...

# Transaction 2 (T2)

def transaction_2():

    global balance

    # Acquire exclusive lock

    # ...

    balance -= 30

    # Release the lock

    # ...

# Execute the transactions concurrently

# ...

Code Explanation:

• Initially, the balance is set to 100.
• Both transactions ('transaction_1' and 'transaction_2') try to access and modify the 'balance' variable.
• Before modifying the balance, each transaction needs to acquire an exclusive lock to ensure that no other transaction can access it.
• After completing the transaction, the exclusive lock is released, allowing other transactions to proceed.

Example 2: Timestamp-Based Concurrency Control

Consider two transactions, T1 and T2, trying to access and update a shared database table called 'orders' with columns 'order_id' and 'status'.

# Python code for timestamp-based concurrency control

# Transaction 1 (T1)

def transaction_1():

    # Set timestamp for T1

    # ...

    # Read data from 'orders' table

    # ...

    # Update 'orders' table

    # ...

# Transaction 2 (T2)

def transaction_2():

    # Set timestamp for T2

    # ...

    # Read data from 'orders' table

    # ...

    # Update 'orders' table

    # ...

# Execute the transactions concurrently

# ...

Code Explanation:

• Each transaction is assigned a unique timestamp (T1 and T2).
• The transactions can read data from the 'orders' table, perform computations, and update the table based on their timestamps.
• The DBMS compares the timestamps of the transactions to detect conflicts and determine the order in which the updates should be applied.

Sample Problems with Solutions

Problem 1: Explain the concept of shared and exclusive locks with an example.

Let's consider a scenario where multiple transactions can read from a database table but only one transaction can modify it at a time.

• Shared Lock: Transaction T1 wants to read from the table.
• Exclusive Lock: Transaction T2 wants to modify the table.

In this case, T1 acquires a shared lock to ensure that it can read the table while T2 is waiting. Once T1 releases the shared lock, T2 acquires an exclusive lock to modify the table.

Problem 2: Describe the purpose of timestamps in concurrency control.

Timestamps are used to order and schedule concurrent transactions in the database. They help identify the order in which transactions were initiated and determine if conflicts occur.

• Transactions with lower timestamps are given priority over transactions with higher timestamps.
• Timestamps allow the DBMS to detect conflicts and resolve them by enforcing a specific order of execution.

Conclusion

Concurrency control is essential in database management systems to ensure data consistency and integrity when multiple users or processes concurrently access and modify the same data. Lock-based and timestamp-based concurrency control mechanisms help prevent conflicts and maintain the overall integrity of the database. By understanding these concepts and applying the appropriate techniques, you can build robust and reliable database systems.
Remember that the examples provided here are simplified for better comprehension. Real-world concurrency control involves more complex mechanisms and considerations. However, this article should give you a solid foundation to explore further and deepen your understanding of concurrency control in DBMS.