Implementing Row Limit Per Partition in Mapping Data Flows
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Refer to the exhibit. You have a Mapping Data Flow in Azure Data Factory that reads JSON files from a folder partitioned by year/month/day. The source setting includes a row limit of 10,000. The sink writes Parquet files with a file pattern and partition columns. You notice that the job processes only the first 10,000 rows from the entire dataset instead of 10,000 rows per partition. How should you modify the data flow to achieve row limit per partition?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Remove the rowLimit from source settings. In the Optimize tab of the source, set 'Partition option' to 'Set partitioning' with 'Value' as 'year,month'. Then add a 'Top N' transformation after the source to limit rows per partition.
Why wrong: Incorrect. Azure Data Factory mapping data flows do not have a 'Top N' transformation. The suggested approach of removing row limit and using 'Set partitioning' plus Top N is not feasible.
B
Add a 'RowNumber' transformation after the source, then filter rows where row number <= 10000 per partition.
Correct. Although there is no explicit 'RowNumber' transformation, the described approach of using a window function to assign row numbers per partition and then filtering is the correct method to limit rows per partition.
C
In the source settings, change rowLimit to a dynamic expression that uses partition variables to limit per partition.
Why wrong: Incorrect. The row limit setting in source options cannot use dynamic expressions based on partition variables; it is a static value.
D
Use a 'Distinct' transformation with 'All columns' to remove duplicate rows, which inherently limits rows.
Why wrong: Incorrect. The Distinct transformation removes duplicate rows but does not limit the number of rows per partition.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Add a 'RowNumber' transformation after the source, then filter rows where row number <= 10000 per partition.
The row limit in source settings applies globally, not per partition. The correct approach is to use a Window transformation to assign a row number per partition (partitioned by the same columns as the folder structure, e.g., year, month) and then filter rows where the row number is <= 10000. Option B describes this method (though 'RowNumber' is not an actual transformation name; it refers to the Window transformation with a row number function). Option A is incorrect because there is no 'Top N' transformation in Azure Data Factory mapping data flows. Option C is incorrect because the row limit setting does not support dynamic expressions based on partition variables. Option D is incorrect because Distinct removes duplicates but does not limit row count.
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.
✗
Remove the rowLimit from source settings. In the Optimize tab of the source, set 'Partition option' to 'Set partitioning' with 'Value' as 'year,month'. Then add a 'Top N' transformation after the source to limit rows per partition.
Why it's wrong here
Incorrect. Azure Data Factory mapping data flows do not have a 'Top N' transformation. The suggested approach of removing row limit and using 'Set partitioning' plus Top N is not feasible.
✓
Add a 'RowNumber' transformation after the source, then filter rows where row number <= 10000 per partition.
Why this is correct
Correct. Although there is no explicit 'RowNumber' transformation, the described approach of using a window function to assign row numbers per partition and then filtering is the correct method to limit rows per partition.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
In the source settings, change rowLimit to a dynamic expression that uses partition variables to limit per partition.
Why it's wrong here
Incorrect. The row limit setting in source options cannot use dynamic expressions based on partition variables; it is a static value.
✗
Use a 'Distinct' transformation with 'All columns' to remove duplicate rows, which inherently limits rows.
Why it's wrong here
Incorrect. The Distinct transformation removes duplicate rows but does not limit the number of rows per partition.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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: Add a 'RowNumber' transformation after the source, then filter rows where row number <= 10000 per partition. — The row limit in source settings applies globally, not per partition. The correct approach is to use a Window transformation to assign a row number per partition (partitioned by the same columns as the folder structure, e.g., year, month) and then filter rows where the row number is <= 10000. Option B describes this method (though 'RowNumber' is not an actual transformation name; it refers to the Window transformation with a row number function). Option A is incorrect because there is no 'Top N' transformation in Azure Data Factory mapping data flows. Option C is incorrect because the row limit setting does not support dynamic expressions based on partition variables. Option D is incorrect because Distinct removes duplicates but does not limit row count.
What should I do if I get this DP-203 question wrong?
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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