In database systems, what is locking and what is one major advantage of using locks during concurrent transactions?

Introduction / Context:
In multi user database systems, many transactions may try to read or write the same data at the same time. Without coordination, this can cause problems such as lost updates, dirty reads, or inconsistent results. Locking is a fundamental concurrency control technique used by relational database management systems to coordinate access and preserve the ACID properties of transactions. This question asks what locking is and highlights one major advantage: maintaining consistency and isolation during concurrent activity.

Given Data / Assumptions:

• We are working with a relational database that supports concurrent transactions.
• Several sessions may try to access the same rows or tables simultaneously.
• The database uses some mechanism to coordinate access to shared data.
• We are focusing on the high level purpose of locking, not on low level lock modes.

Concept / Approach:
Locking temporarily restricts access to data items while a transaction is performing operations on them. Depending on the isolation level and database engine, locks can be shared for read operations or exclusive for write operations. The key advantage is preventing conflicting operations from corrupting data or creating inconsistent results. When a transaction holds an exclusive lock on a row, other transactions usually cannot modify that row until the lock is released. A correct answer must reference concurrency control and data consistency, not unrelated features such as encryption or desktop window management.

Step-by-Step Solution:
Step 1: Recall that locking is about controlling concurrent access to the same data items. Step 2: Examine Option A, which states that locking is a concurrency control mechanism that temporarily restricts access to data items so that transactions do not interfere with each other, helping to maintain consistency and isolation. This matches standard database theory. Step 3: Examine Option B, which equates locking with permanent encryption; this is not correct. Step 4: Examine Option C, which describes a backup technique; backup is a separate concern. Step 5: Examine Option D, which refers to user interface windows; this is not related to database locking. Step 6: Examine Option E, which describes logging; while logs record activity, they do not control access to data. Step 7: Conclude that Option A is the only option that correctly defines locking and its advantage.

Verification / Alternative check:
Database textbooks and vendor documentation explain that locks are acquired and released as part of transaction processing. Isolation levels such as read committed and serializable are implemented using locks and other mechanisms. Examples show that without locks, two concurrent updates might overwrite each other, leading to lost updates. With locking enabled, the second transaction waits until the first commits or rolls back, preserving consistency. None of the alternative descriptions in the other options match these behaviors.

Why Other Options Are Wrong:

• Option B is wrong because encryption protects confidentiality but does not coordinate concurrent access.
• Option C is wrong because backups are about durability and disaster recovery, not concurrency control.
• Option D is wrong because desktop window behavior has no relation to database locks.
• Option E is wrong because logging records what happened but does not prevent conflicting operations from happening.

Common Pitfalls:
A common pitfall is to assume that more locking is always better. Excessive locking or overly strict isolation levels can lead to contention and deadlocks. Another mistake is to ignore lock contention when investigating performance issues. Administrators and developers should understand how their database uses locks and design transactions to be as short and efficient as possible while still preserving correctness.

Final Answer:
The correct definition and advantage are given in Option A: Locking is a concurrency control mechanism that temporarily restricts access to data items so that transactions do not interfere with each other, helping to maintain consistency and isolation.