Question

Suppose one transaction tries to add \(\$ 100\) to an account whose balance is \(\$ 200\) while another tries to withdraw \(\$ 100\) from the same account. Describe an interweaving of these transactions that would lead to a final balance of \(\$ 100\). Describe an interweaving of these transactions that would lead to a final balance of \(\$ 300\).

Short answer

Final balance of \(\$ 100\): withdrawal only; final balance of \(\$ 300\): deposit only.

Step-by-step solution

Initial Balance

Start with the initial balance of the account, which is \(\$ 200\).

Step 2a: Withdrawing \(\$ 100\) First

Let's consider the scenario where the withdrawal transaction occurs first. This transaction takes \(\\( 100\) from the account, resulting in a balance of \(\\) 200 - \\( 100 = \\) 100\).

Step 3a: Adding \(\$ 100\) After Withdrawal

Next, the deposit transaction occurs, adding \(\\( 100\) to the account. The balance becomes \(\\) 100 + \\( 100 = \\) 200\).

Step 4a: Conclusion for Final Balance of \(\$ 100\)

For a final balance of \(\$ 100\), the withdrawal must happen, and no further transaction should take place.

Step 2b: Adding \(\$ 100\) First

Now consider the scenario where the deposit transaction happens first. This adds \(\\( 100\) to the account, so the balance becomes \(\\) 200 + \\( 100 = \\) 300\).

Step 3b: Withdrawing \(\$ 100\) After Deposit

Then the withdrawal transaction occurs, leading to \(\\( 300 - \\) 100 = \$ 200\).

Step 4b: Conclusion for Final Balance of \(\$ 300\)

To achieve a final balance of \(\\( 300\), ensure that the deposit of \(\\) 100\) happens without the withdrawal taking place.

Key concepts

Concurrency Control

Concurrency control is essential in database systems to maintain consistency and isolation for transactions happening at the same time. When multiple transactions access and potentially change the same data simultaneously, problems can arise. Without appropriate mechanisms, you might end up with incorrect or unexpected results, such as having an account balance that isn't accurate.

To prevent such issues, concurrency control techniques, like locks, timestamps, and logs, coordinate transaction processes. These methods help to ensure end users receive consistent and correct data.

• Locks: Locks prevent other transactions from accessing affected data until the lock is released.
• Timestamps: Orders transactions to reduce conflicts, allowing earlier transactions to influence the outcome of later ones.
• Logs: Record changes about to happen, allowing a rollback to previous states if needed.

Concurrency control, therefore, makes sure that your account updates go through smoothly, whether adding or withdrawing funds.".

Transaction Interweaving

Transaction interweaving refers to the sequence and overlap of transactions within a database system. Depending on how transactions are interwoven, the final results can differ significantly. Consider the scenario from the exercise: a transaction process involving one withdrawal and one deposit. Interweaving these two transactions in different orders can lead to different outcomes.

Let's look at these two interweaving examples:

• Sequential Transaction: If the withdrawal happens before the deposit, the final balance will differ from if the deposit occurs first.
• Simultaneous Processing: Not managing the sequence properly could lead to only one transaction being applied or both collisions, which might mean inaccurate final balances.

Proper transaction management ensures sequences that maintain data consistency, protecting the accuracy of account balances.

Data Consistency

Data consistency is pivotal for maintaining the correctness of a database over transactions. A database remains 'consistent' if it accurately reflects the real-world situation it models, regardless of the transactions processed.

In the example scenario, assuring data consistency means the account balance should logically reflect the transactions conducted—whether adding or subtracting amounts. Without consistency, our closing balance could untruthfully indicate funds that do not tally with real transactions.

• Constraints: Rules, such as ensuring no account balance can go negative, enforce consistency.
• Validation: Systems continually check that processed data stays within set parameters and aligns with all other aspects of the database.

When data consistency is prioritized, users trust that their account balances will always represent the true state, even amidst multiple interwoven transactions.