Design Movie Rental System
A hard-tier problem at 36% community acceptance, tagged with Array, Hash Table, Design. Reported in interviews at Flipkart and 0 others.
Design Movie Rental System is a hard-tier system design problem that appears in Flipkart interviews. You're building a backend for tracking movie rentals, prices, and customer orders. The trick isn't just storing data, it's retrieving it fast under specific constraints. You need efficient structures to track which movies are available, what customers owe, and which rentals are most profitable. Most candidates tank this because they conflate 'getting the data' with 'getting it in the right order.' If this problem hits your live OA and you blank on the heap ordering or hash table layout, StealthCoder surfaces a working solution invisibly while you're on screen share.
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Design Movie Rental System is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoderThe core pattern is layering multiple data structures to serve different queries fast. You'll need a Hash Table to map movies and customers to their state, a Heap (Priority Queue) to rank rentals by price or deadline, and an Ordered Set or sorted container to return results in the required order. The gotcha: a naive single-pass solution works but times out because you're re-sorting on every query. The winning approach uses pre-sorted lookups via heap pops or segment trees, depending on the exact constraints your interviewer specifies. Most candidates underestimate the cardinality, they assume small datasets and ignore index efficiency. StealthCoder is the hedge when the interviewer asks for 'top N rentals by price' and you realize your in-memory sort is O(n log n) per call on a hot path.
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Design Movie Rental System recycles across companies for a reason. It's hard-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Design Movie Rental System interview FAQ
Is this actually asked at Flipkart, or is it rare?+
Flipkart reports this problem. Acceptance sits at 35.5%, so roughly two-thirds of candidates don't ship a complete solution. That's usually because they nail the data model but botch the query layer. It's a real ask, not a ghost problem.
What's the trick I'm missing?+
The aha moment: you can't rebuild your answer structure on every query. Pre-compute or use a heap to lazily materialize results in sorted order. Hash tables give you O(1) lookups, but heaps give you O(log n) sorted results without full re-sorting each time.
Do I really need an Ordered Set, or is a Heap enough?+
Depends on your query pattern. A Heap excels when you only need the top K items. An Ordered Set (like a balanced BST or skip list) is better if you need range queries or frequent updates. In most Flipkart versions, Heap is the faster play.
What kills most solutions in the real interview?+
Forgetting that hash lookups are O(1) for exact keys but don't give you sorted order for free. Candidates code a solution that works on tiny test cases, then tank when the OA loads 100k rentals and asks for top 10 by revenue.
How does this connect to the other topics, Array and Hash Table?+
Array is your underlying storage; Hash Table is your index layer for O(1) customer and movie lookups. The Heap and Ordered Set are your query optimization layers. All five topics work together, not separately.
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