Day 40 — Task Scheduler
Coding problem
| Problem | Task Scheduler |
| LeetCode ID(s) | LeetCode #621 |
| Difficulty | Medium |
| Pattern | Greedy / Heap |
| Company tags | Meta |
| Suggested time | 20m |
Solution outline (coding)
Focus on the Greedy / Heap 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
tasks(task_id, type, duration). BigQuery: design a schedule report that groups tasks to minimize CPU idle time; focus on how inputs/outputs are modeled, not algorithm details.
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.