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Data platform · Pipelines

Late data

Mediumplatform-05
late dataevent timewatermarksreprocessing

Question

What is late data, and how do pipelines handle it?

Solution

Late data arrives after you already processed the time window it belongs to. Example: an event with event_time=10:01 shows up at 12:40 because a mobile app was offline.

window 10:00-11:00 closed at 11:05
late event for 10:15 arrives at 12:40  -> needs a policy

Common strategies

  • Watermarks (streaming): wait a grace period, then close the window
  • Allowed lateness: update aggregates for a while after the window
  • Recompute partitions: nightly job rebuilds yesterday with all arrivals
  • Separate late path: write corrections / adjustments instead of rewriting everything

Batch angle

Even daily jobs see late data: a file for ds=2026-09-04 arriving on Sept 6. Idempotent partition rebuilds or merge-on-key fix this.

Interview tip: Distinguish event time vs processing time, then give one streaming (watermark) and one batch (partition rebuild) answer.

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