Implement Stream Windowing
tumbling, sliding and session windows
Challenge 3 of Data PipelinesAdvanced~55 min
Turn an endless stream of events into finite chunks you can aggregate. Windowing is how stream processors compute things like 'requests per minute' over data that never ends. Build the three canonical window types: tumbling (fixed, non-overlapping), sliding (overlapping), and session (gap-based), plus the per-window aggregation. The bucketing logic inside Flink, Kafka Streams, and Spark Structured Streaming.