hardMultiple ChoiceObjective-mapped
PDE Practice Question: A company runs a production Dataflow streaming…
A company runs a production Dataflow streaming pipeline that reads from Pub/Sub, groups events by customer ID, and writes to BigQuery. The pipeline uses global windows with triggers. After a recent code change, the pipeline started generating duplicate events in BigQuery for the same customer ID. The previous version did not have duplicates. The team reviews the code and sees that the trigger was changed from 'afterProcessingTime' to 'afterWatermark'. What is the most likely reason for duplicates?
⚠ Common exam trap
Google Cloud often tests the distinction between processing-time and event-time triggers, and the trap here is that candidates assume `afterWatermark` is simply a 'one-time' trigger, overlooking that late-arriving data can cause additional firings.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Late-arriving events cause the afterWatermark trigger to fire additional panes for the same window
The change from `afterProcessingTime` to `afterWatermark` introduces a dependency on the watermark, which estimates event time progress. When late-arriving events (those with timestamps before the watermark) arrive after the watermark has advanced, the `afterWatermark` trigger fires an additional pane for the same window, causing duplicate writes to BigQuery. The previous trigger (`afterProcessingTime`) fired based on processing time, which does not react to late data in the same way, hence no duplicates.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The afterProcessingTime trigger fired multiple times for the same window
Why it's wrong here
Processing time triggers do not cause duplicates based on late data.
- ✓
Late-arriving events cause the afterWatermark trigger to fire additional panes for the same window
Why this is correct
Watermark triggers can fire again for late data, producing duplicates if not deduplicated.
- ✗
The pipeline is firing early and on-time panes for the same window
Why it's wrong here
Early and on-time firings are separate; duplicates only if late data triggers additional panes.
- ✗
The pipeline uses accumulation mode which accumulates results across firings
Why it's wrong here
Accumulation mode can cause duplicates, but the trigger change is the key factor.
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