DE Applications: Rate Limiting, Sessionization, and Top-K Deque

Concepts: pyRateLimiter, pySessionization, pyMonotonicDeque

The intermediate sliding window problems you have learned in this lesson are not just interview exercises. They map directly to production DE patterns that senior engineers implement regularly. When you close your LeetCode tab and open a Kafka Streams job or a Flink application, the same algorithmic building blocks are there: variable-size time windows, frequency maps over event streams, and sliding deques for top-K queries. Knowing how to bridge the interview problem to the production system is what gets senior engineers the 'strong hire' signal. Let me walk you through three patterns that are directly asked about in DE system design rounds. Rate Limiting Over Rolling Time Windows The sliding window rate limiter is the production-grade approach used by Stripe, Cloudflare, and most serious