Heap / Priority Queuehard70 minMobile Engineer

Cache Real-Time Top-K Prioritizer

Mobile Engineer signal: heap + top-k in a local cache eviction context. This is a ProdMatch-owned mobile engineer drill, framed as a March 2026 Myntra App Performance simulation, not a copied platform question.

Company context

Myntra · App Performance

Freshness

March 2026

Product surface

local cache eviction

ProdMatch interview simulation based on product-team patterns; not a claim of a real company question.

Question

Your App Performance team needs a live top-k view for entries. Each update changes an item's score. Return the current top k item IDs after each update, ordered by score desc then ID asc.

Input

Initial scores, k, and update stream [id, delta].

Output

Top-k IDs after every update.

Constraints

1 <= items <= 200000
1 <= updates <= 200000
Scores can be negative.

Concepts

offline sync
local cache
gesture streams
heap
top-k
streaming rank

scores: [5,1,3], k=2, update [1,+5] -> [1,0]

Approach

Try framing your own approach first. The 30 seconds you think before peeking is where learning happens.

Clean Solution

Reveal the approach first.

How well did you understand?

Your rating tunes when this problem shows up again.

Common Mistakes

Use a stable tie-breaker for equal scores.
Do not sort the full stream when k is small.

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