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Dynamic Programming / 1Dmedium45 minData Engineer

Watermark Ranking Budget Optimizer

Data Engineer signal: dynamic programming + knapsack in a stream watermarking context. This is a ProdMatch-owned data engineer drill, framed as a March 2026 ServiceNow Realtime Data simulation, not a copied platform question.

Company context

ServiceNow · Realtime Data

Freshness

March 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 roadmap has candidate improvements for stream watermarking. Each improvement has cost, lift and risk. Maximize lift under budget while keeping total risk below a threshold.

Input

  • Items [cost, lift, risk], budget and maxRisk.

Output

  • Maximum lift achievable.

Constraints

  • 1 <= items.length <= 500
  • Budget <= 10000
  • maxRisk <= 10000

Concepts

  • stream windows
  • watermarks
  • lineage DAGs
  • dynamic programming
  • knapsack
  • ranking trade-off

items [[2,5,1],[4,9,4]], budget=4, risk=4 -> 9

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

  • Unclear state definition usually causes off-by-one bugs.
  • Do not overwrite a state before all consumers have used it.

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