DP-203 Develop data processing Practice Question
Which TWO of the following are valid ways to handle late-arriving data in a streaming solution with Azure Stream Analytics? (Choose two.)
⚠ Common exam trap
It's easy for candidates to confuse the 'late arrival tolerance' with a simple delay setting, not realizing it is a reordering buffer up to 21 days, and they overlook temporal joins as a valid pattern for handling late data, instead assuming only external functions or full reprocessing are options.
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 'late arrival tolerance' window in the event ordering settings up to 21 days.
Azure Stream Analytics allows you to configure a 'late arrival tolerance' window in the event ordering settings, which can be set up to a maximum of 21 days. This window defines how long the service will wait to accommodate events that arrive after their timestamp, reordering them within that tolerance before processing. Option E is correct because a temporal join (e.g., using LATERAL or JOIN with DATEDIFF) can combine a late-arriving event with historical data from a reference or stream window, enabling you to retroactively correct aggregations or state.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reprocess the entire stream from the beginning when late data is detected.
Why it's wrong here
Reprocessing is inefficient and not recommended; Stream Analytics handles late data within tolerance.
- ✗
Implement a custom Azure Function as a 'LateDataHandler' in the query.
Why it's wrong here
There is no built-in concept of a late data handler; custom functions are for complex logic, not for late arrival management.
- ✗
Use a reference data input to store late-arriving events.
Why it's wrong here
Reference data is static and not intended for streaming events.
- ✓
Configure the 'late arrival tolerance' window in the event ordering settings up to 21 days.
Why this is correct
Stream Analytics allows setting a late arrival tolerance window to handle events that arrive after the event time.
- ✓
Use a temporal join to combine the late-arriving event with the historical window.
Why this is correct
Temporal joins allow joining events from different time windows, enabling late data integration.
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