Reorder Search Results for Provider Diversity
Company: Mavenclinic
Role: Backend Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Onsite
Build a function that paginates ordered provider listings for a telehealth marketplace.
Each input record is a CSV string in the format:
`provider_id, listing_id, rating, consultation_fee, city`
Example record:
`1,101,4.9,100,NYC`
The input list is already sorted by relevance. A single provider may have multiple listings. Reorder the listings into pages of size 5 with these rules:
- Within a page, include at most one listing from the same provider whenever possible.
- Preserve the original order as much as possible. In other words, when selecting the next valid result, prefer the earliest remaining listing.
- If there are not enough distinct providers to fill a page, allow repeated providers to fill the remaining slots.
- Return or print the results page by page, with a blank line between pages.
Example input:
`['1,101,4.9,100,NYC', '2,102,4.8,120,LA', '1,103,4.7,95,Boston', '3,104,4.6,110,Chicago']`
Discuss the time and space complexity. Then discuss two follow-ups:
1. How would you change the algorithm if high-scoring providers were allowed to appear multiple times on the same page?
2. How would you implement a memory-efficient streaming version when the input can contain roughly 150 million listings and does not fit in memory?
Overview: This question evaluates algorithmic problem-solving and systems-level thinking for reordering and paginating ordered listings while enforcing provider-diversity constraints, testing competencies in stable selection strategies, data-structure usage, complexity analysis, and memory-efficient streaming techniques; it is in the Coding & Algorithms domain for backend engineering. It is commonly asked to assess a candidate's ability to balance ordering stability with fairness constraints, reason about time/space trade-offs for large-scale inputs, and demonstrate both practical implementation skills and conceptual understanding of algorithmic complexity and streaming design.