Handle Late Data in Streaming

HardPipelines00:00

Practice interviewer

In session

5 left

00:00

Your question is Handle Late Data in Streaming. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

You need to log in / sign up to chat or submit.

Problem

You are designing a streaming pipeline where some events arrive after their event time. Those late records can invalidate previously computed windows, aggregates, or fact tables. The goal is to keep downstream data correct while limiting unnecessary recomputation.

What this tests

Event-time processing and watermark design
Idempotent writes and deduplication
Repair strategy for very late records
Data quality controls for corrected outputs

Key design signals

Common trade-off·Longer watermark vs lower latencyRecovery pattern·Targeted backfill instead of full replayPrimary challenge·Correctness under out-of-order arrival