Day 86 — Version-Controlled Data Structure
Coding problem
| Problem | Version-Controlled Data Structure |
| LeetCode ID(s) | — |
| Difficulty | Medium |
| Pattern | Design / Build |
| Company tags | OpenAI |
| Suggested time | 30m |
Solution outline (coding)
Focus on the Design / Build pattern. Start by writing out a few examples by hand, then identify the invariant you must maintain (e.g., prefix sums, window bounds, visited set, heap ordering). Aim for an implementation you can explain in under a minute, including time and space complexity.
Show Python solution
# Solution template based on the main pattern for this day.
# Replace this with your final, production-ready solution as you practice.SQL question
versioned_data(entity_id, version, payload, ts). BigQuery: design queries to retrieve latest consistent version at time T and audit version history per entity.
How to approach (SQL)
Break the prompt into steps:
- Identify source tables, required joins, and filters (especially on time partitions).
- Decide where you need GROUP BY vs. window functions (e.g.,
ROW_NUMBER,SUM() OVER,COUNT() OVER). - For BigQuery, think about partitioning and clustering to avoid unnecessary full scans.
- Write the query in stages (CTEs) so each step is easy to debug and reason about. Finish by checking edge cases: nulls, late events, duplicated keys, and extreme values.