Heap / Priority Queuehard70 minAI/ML Engineer

Recommend Real-Time Top-K Prioritizer

AI/ML Engineer signal: heap + top-k in a recommendation system context. This is a ProdMatch-owned ai ml engineer drill, framed as a March 2026 SAP Labs Personalization ML simulation, not a copied platform question.

Company context

SAP Labs · Personalization ML

Freshness

March 2026

Product surface

recommendation system

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

Question

Your Personalization ML team needs a live top-k view for candidates. 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.

Next Similar Problems

Vector Real-Time Top-K Prioritizerhard GraphRAG Real-Time Top-K Prioritizerhard Batching Real-Time Top-K Prioritizerhard