Heap / Priority Queuehard70 minData Engineer

Watermark Real-Time Top-K Prioritizer

Data Engineer signal: heap + top-k in a stream watermarking context. This is a ProdMatch-owned data engineer drill, framed as a April 2026 Razorpay Realtime Data simulation, not a copied platform question.

Company context

Razorpay · Realtime Data

Freshness

April 2026

Product surface

stream watermarking

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

Question

Your Realtime Data team needs a live top-k view for events. 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

stream windows
watermarks
lineage DAGs
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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