easyMultiple ChoiceObjective-mapped
PDE Practice Question: Designing a real-time clickstream analytics…
A company is designing a real-time clickstream analytics pipeline using Pub/Sub and Dataflow. The pipeline must handle late-arriving data (up to 1 hour) and ensure exactly-once processing. Which Dataflow feature should be configured to handle late data correctly?
⚠ Common exam trap
Google Cloud often tests the distinction between allowed lateness (which extends window lifetime for late data) and watermark estimation (which is a system property, not a user-set parameter), leading candidates to incorrectly choose D.
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
✓
Configure the trigger with allowed lateness of 1 hour.
Dataflow's allowed lateness feature explicitly controls how long the pipeline waits for late-arriving data before closing a window. By setting allowed lateness to 1 hour, the watermark is held back, and late data within that period is still processed with exactly-once semantics. This directly addresses the requirement for handling late data up to 1 hour while ensuring no duplicates or data loss.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure the trigger with allowed lateness of 1 hour.
Why this is correct
Allowed lateness specifies how long after the watermark the system waits for late data before considering the window complete.
- ✗
Use fixed windows with a 1-hour period and enable data discarding.
Why it's wrong here
Data discarding would drop late data; the requirement is to handle it, not discard.
- ✗
Use session windows with a gap duration of 1 hour.
Why it's wrong here
Session windows group events that occur within a gap; they don't specifically handle late arrivals after the watermark.
- ✗
Set the watermark estimate to 1 hour.
Why it's wrong here
Watermarks estimate progress but don't automatically handle late data; they only track event time progress.
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