Day 69 — Sliding Window Maximum
Coding problem
| Problem | Sliding Window Maximum |
| LeetCode ID(s) | LeetCode #239 |
| Difficulty | Hard |
| Pattern | Monotonic Deque |
| Company tags | |
| Suggested time | 25m |
Solution outline (coding)
Focus on the Monotonic Deque 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
metrics(ts, value). BigQuery: implement sliding window maximum over fixed-size time windows with window functions and ARRAYs; compare cost vs application-level computation.
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.