Binary Searchmedium45 minData Engineer

Schema Minimum Feasible Throughput

Data Engineer signal: binary search on answer + monotonic predicate in a schema evolution context. This is a ProdMatch-owned data engineer drill, framed as a April 2026 Uber Data Contracts simulation, not a copied platform question.

Company context

Uber · Data Contracts

Freshness

April 2026

Product surface

schema evolution

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

Question

For schema evolution, choose the minimum processing rate so all versions finish before deadline. Each worker can process rate units per minute, rounded up per item.

Input

Work item sizes and deadline minutes.

Output

Minimum integer rate.

Constraints

1 <= items.length <= 200000
1 <= item size <= 1e9
Deadline is at least items.length.

Concepts

stream windows
watermarks
lineage DAGs
binary search on answer
monotonic predicate

sizes [3,6,7,11], deadline=8 -> 4

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 low + (high - low) // 2 to avoid overflow.
The predicate must be monotonic or binary search is invalid.

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