- A
The job is not handling late-arriving events.
Why wrong: Late events cause out-of-order but not duplicates.
- B
The job is being restarted and reprocessing data.
Restart can cause reprocessing and duplicate output without idempotent writes.
- C
The input event hub is receiving duplicate events.
Why wrong: Input is stated as unique.
- D
The tumbling window size is too small.
Why wrong: Window size does not cause duplicates.
Question 842 of 851
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability 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
✓
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that 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.
Detailed technical explanation
How to think about this question
Under the hood, Azure Stream Analytics uses checkpointing to ensure exactly-once processing semantics, but when a job is restarted (e.g., due to a scaling operation or failure), it may resume from the last saved checkpoint or from a specified start time. If the output adapter (Azure SQL Database) does not support idempotent writes, the same aggregated results can be inserted multiple times. In real-world scenarios, this often occurs during job updates or when the 'When last stopped' start option is used, leading to unintended reprocessing of historical data.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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