Design Insert/Delete/GetRandom with Weighted Sampling
Company: Hudson River Trading
Role: Software Engineer
Category: Software Engineering Fundamentals
Difficulty: medium
Interview Round: Technical Screen
Design a data structure that supports inserting values, deleting values, and returning a random value. Then extend it so each inserted value has a weight and `getRandom` returns values with probability proportional to weight.
### Constraints & Assumptions
- Values are unique unless clarified.
- Unweighted operations should be O(1) average time.
- Weighted sampling can be O(log n) unless the interviewer requires O(1).
- Weights are positive numbers.
### Clarifying Questions to Ask
- Can duplicate values be inserted?
- Do weights change after insertion?
- Are random calls much more frequent than updates?
- Is exact weighted probability required?
- What language and random library are available?
### What a Strong Answer Covers
```premium-lock What a Strong Answer Covers
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### Follow-up Questions
- How would you support duplicate values?
- How would you update a weight?
- How would you test random distribution?
- When would alias tables be better than Fenwick trees?
Quick Answer: This Hudson River Trading software engineering question combines insert, delete, random access, and weighted sampling in one data structure design. It is useful preparation for interviews that probe invariants, expected complexity, and how to maintain auxiliary state correctly.