Reservation and hold system in LLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Architecture

intermediate

Identify the correct component for handling reservation expiration

In a reservation and hold system, which component is best suited to automatically release held items after a timeout period?

A The user interface component that prompts users to release holds manually.

B A background scheduler service that tracks hold expiration and releases items.

C The database triggers that delete hold records after a fixed time.

D The payment gateway that cancels holds if payment is not received.

💡 Hint

Think about which part can run tasks independently and periodically.

A background scheduler service can run timed tasks to check and release expired holds automatically, ensuring system consistency without user intervention.

❓ scaling

intermediate

Scaling holds in a high-traffic reservation system

Which approach best supports scaling the hold feature in a reservation system with millions of concurrent users?

A Store hold states in a distributed in-memory cache with TTL (time-to-live) support.

B Keep all hold data only in a single relational database instance.

C Use local session storage on user devices to track holds.

D Write hold information directly to log files for later processing.

💡 Hint

Consider fast access and automatic expiration for large scale.

Distributed in-memory caches with TTL allow fast reads/writes and automatic expiration of holds, which is essential for scaling to millions of users.

❓ tradeoff

advanced

Tradeoff between consistency and availability in hold release

In a distributed reservation system, what is the main tradeoff when choosing to release holds immediately versus eventually?

A Eventual release guarantees immediate availability but sacrifices data durability.

B Immediate release improves availability but causes stale data inconsistencies.

C Immediate release favors consistency but may reduce availability during network issues.

D Eventual release ensures strong consistency but delays user feedback.

💡 Hint

Think about how quickly the system updates state and handles failures.

Releasing holds immediately requires strong coordination, which can reduce availability if parts of the system are unreachable, but it keeps data consistent.

🧠 Conceptual

advanced

Understanding idempotency in hold requests

Why is idempotency important when processing hold requests in a reservation system?

A It guarantees that holds never expire automatically.

B It ensures holds are always released after a fixed timeout.

C It allows multiple users to hold the same item simultaneously.

D It prevents duplicate holds when the same request is retried due to network errors.

💡 Hint

Consider what happens if a request is sent multiple times.

Idempotency ensures that retrying the same hold request does not create multiple holds or inconsistent states, which is critical in unreliable networks.

❓ estimation

expert

Estimating capacity for hold expiration processing

A reservation system expects 10 million holds daily, each expiring after 15 minutes if not confirmed. How many hold expirations must the system process per second on average?

A Approximately 11,574 expirations per second.

B Approximately 1,157 expirations per second.

C Approximately 6,944 expirations per second.

D Approximately 694 expirations per second.

💡 Hint

Calculate total seconds in 15 minutes and divide total holds by that.

15 minutes = 900 seconds. 10,000,000 holds / 900 seconds = 11,111 holds per second. The closest option is 11,574 expirations per second.