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This question evaluates algorithm design and analysis skills, including selection under sum constraints with negatives and zeros, streaming and query-preprocessing strategies for repeated budgets, and number-theoretic factor enumeration for large N, all within the Coding & Algorithms domain.

  • hard
  • Amazon
  • Coding & Algorithms
  • Data Scientist

Solve subset-count and kth-factor problems

Company: Amazon

Role: Data Scientist

Category: Coding & Algorithms

Difficulty: hard

Interview Round: Take-home Project

You will solve two independent tasks: A) Maximum count under sum constraint: Given an array of integers arr and an integer n, return the maximum number of elements you can choose such that their sum ≤ n. Output only the count. Constraints: 1 ≤ |arr| ≤ 200000, −1e9 ≤ arr[i] ≤ 1e9, and n fits in 64-bit signed integer. Requirements: design an algorithm that is optimal for the case where all arr[i] ≥ 0; handle zeros and negative numbers correctly; analyze time and space complexity; prove correctness for the non‑negative case; and describe how you would support Q up to 100000 queries with different n on the same static arr. Follow‑ups: What changes if arr arrives as a stream you cannot fully store? Provide a strategy with at most ±1 error in the count and justify it. B) Find the Kth factor: Given positive integers N and K (1‑indexed), return the Kth factor of N in ascending order; if fewer than K factors exist, return −1. Optimize for N up to 10^12. Discuss an O(√N) solution that avoids duplicate factors when N is a perfect square and analyze time/space trade‑offs.

Quick Answer: This question evaluates algorithm design and analysis skills, including selection under sum constraints with negatives and zeros, streaming and query-preprocessing strategies for repeated budgets, and number-theoretic factor enumeration for large N, all within the Coding & Algorithms domain.

Maximum Count Under Sum Constraint

Return the maximum number of elements whose sum is at most budget.

Examples

Input: ([1, 2, 3], 3)

Expected Output: 2

Explanation: Can select 1 and 2.

Input: ([0, 0, 5], 0)

Expected Output: 2

Explanation: Zeros count.

Input: ([-5, 10, 11], 5)

Expected Output: 2

Explanation: Negative helps budget.

Input: ([5, 6], 4)

Expected Output: 0

Explanation: No selection.

Hints

  1. For any k, the k smallest elements minimize the sum among k selected elements.

Kth Factor

Return the K-th positive factor of N in ascending order, or -1 if it does not exist.

Examples

Input: (12, 3)

Expected Output: 3

Explanation: Factors 1,2,3,4,6,12.

Input: (7, 2)

Expected Output: 7

Explanation: Prime.

Input: (16, 3)

Expected Output: 4

Explanation: Avoid duplicate square root.

Input: (10, 5)

Expected Output: -1

Explanation: Too few factors.

Last updated: Jun 27, 2026

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