Heap / Priority Queuehard70 minAI/ML Engineer

GraphRAG Real-Time Top-K Prioritizer

AI/ML Engineer signal: heap + top-k in a knowledge graph RAG context. This is a ProdMatch-owned ai ml engineer drill, framed as a April 2026 Apple AI Search simulation, not a copied platform question.

Company context

Apple · AI Search

Freshness

April 2026

Product surface

knowledge graph RAG

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

Question

Your AI Search team needs a live top-k view for entities. 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

vector search
RAG retrieval
recommendation graphs
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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