Implement event-time windowing in Kafka Streams using stream-time punctuators and suppress to emit only final window results

Steps

1. Build a KStream with a TimeWindows.ofSizeWithNoGrace(Duration.ofMinutes(5)) window; note that noGrace means late records are dropped, which is appropriate when downstream consumers cannot handle updates
2. For use cases requiring late-record acceptance, use TimeWindows.ofSizeAndGrace(Duration.ofMinutes(5), Duration.ofSeconds(30)) to allow a 30-second grace period
3. Chain .suppress(Suppressed.untilWindowCloses(Suppressed.BufferConfig.unbounded())) after the aggregation to hold results until the window is closed and emit only the final value
4. Understand that suppress uses stream time (max observed event timestamp) to close windows, not wall-clock time — if the input stream goes idle, windows will never close; add a punctuator as a fallback heartbeat
5. Configure commit.interval.ms and cache.max.bytes.buffering to control how frequently intermediate results flush before suppression fires
6. Test by injecting out-of-order events and confirming only one downstream record per window key appears after the grace period expires