DP-203 Develop data processing Practice Question
You are using Azure Stream Analytics to process real-time temperature data from IoT devices. The output must be written to Azure SQL Database. The job has been running successfully for weeks, but recently you notice that the output data has duplicate rows. The input events are unique. The job uses a windowed aggregation (TumblingWindow). What is the most likely cause of duplicates?
⚠ Common exam trap
Candidates often assume duplicates are caused by late-arriving events or input issues, but the core concept is that job restarts in Stream Analytics can reprocess data, and without idempotent output, duplicates are introduced.
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
✓
The job is being restarted and reprocessing data.
When an Azure Stream Analytics job is restarted, it may reprocess data from the last checkpoint or from the beginning of the input stream, depending on the configured start time and output policy. This reprocessing can cause duplicate rows in the output, especially when using windowed aggregations like TumblingWindow, because the same events are aggregated again and written to Azure SQL Database without deduplication logic.
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 job is not handling late-arriving events.
Why it's wrong here
Late events cause out-of-order but not duplicates.
- ✓
The job is being restarted and reprocessing data.
Why this is correct
Restart can cause reprocessing and duplicate output without idempotent writes.
- ✗
The input event hub is receiving duplicate events.
Why it's wrong here
Input is stated as unique.
- ✗
The tumbling window size is too small.
Why it's wrong here
Window size does not cause duplicates.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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