- A
Enable staging and use PolyBase or COPY statement for the copy activity.
Staging with PolyBase/COPY allows data to be copied in parallel and avoids timeouts.
- B
Decrease the 'writeBatchSize' to 1000.
Why wrong: Decreasing batch size reduces throughput and may increase duration.
- C
Increase the 'timeout' value in the copy activity settings.
Why wrong: Increasing timeout may delay failure but does not address the root cause of long-running queries.
- D
Use a query with 'queryTimeout' set to 7200 seconds.
Why wrong: Query timeout is for source query execution, not for copy activity timeout.
Question 671 of 851
Staging with PolyBase in Azure Data Factory Copy Activity — Resolve Timeout | Azure Data Engineer Associate Explained
This DP-203 practice question tests your understanding of develop data processing. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 monitoring an Azure Data Factory pipeline that runs every hour. The pipeline uses a Copy activity to copy data from Azure SQL Database to Azure Blob Storage. Recently, the pipeline has been failing with a 'Timeout' error. The source SQL database has a large number of records. What should you do to resolve the timeout?
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
✓
Enable staging and use PolyBase or COPY statement for the copy activity.
Option A is correct because enabling staging with PolyBase or the COPY statement offloads the data transfer to Azure Data Lake or Blob Storage, bypassing the bottleneck of the Copy activity's default data movement. This approach is specifically designed for large-scale data loads from Azure SQL Database, as it uses the database's bulk export capabilities and avoids the timeout by not relying on the Copy activity's internal query execution.
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.
- ✓
Enable staging and use PolyBase or COPY statement for the copy activity.
Why this is correct
Staging with PolyBase/COPY allows data to be copied in parallel and avoids timeouts.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the 'writeBatchSize' to 1000.
Why it's wrong here
Decreasing batch size reduces throughput and may increase duration.
- ✗
Increase the 'timeout' value in the copy activity settings.
Why it's wrong here
Increasing timeout may delay failure but does not address the root cause of long-running queries.
- ✗
Use a query with 'queryTimeout' set to 7200 seconds.
Why it's wrong here
Query timeout is for source query execution, not for copy activity timeout.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume increasing timeouts (options C or D) will fix the issue, but the real problem is the Copy activity's default command timeout limitation, which requires a fundamentally different data movement approach like staging with PolyBase or COPY statement.
Detailed technical explanation
How to think about this question
Under the hood, the Copy activity uses a default command timeout of 30 seconds for source queries against Azure SQL Database, which can be exceeded when scanning large tables. Enabling staging with PolyBase or the COPY statement leverages the database's native bulk export (e.g., using 'bcp' or the COPY INTO command) to write data directly to Blob Storage, bypassing the Copy activity's row-by-row or batch retrieval. In real-world scenarios, this approach also reduces DTU consumption on the source database and improves throughput for incremental loads.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Visual reference
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
What to study next
Got this wrong? Here's your next step.
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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: Enable staging and use PolyBase or COPY statement for the copy activity. — Option A is correct because enabling staging with PolyBase or the COPY statement offloads the data transfer to Azure Data Lake or Blob Storage, bypassing the bottleneck of the Copy activity's default data movement. This approach is specifically designed for large-scale data loads from Azure SQL Database, as it uses the database's bulk export capabilities and avoids the timeout by not relying on the Copy activity's internal query execution.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways this is tested on DP-203
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Refer to the exhibit. You have an Azure Data Factory pipeline that copies data from Azure Blob Storage to Azure SQL Database. The copy activity uses a preCopyScript to truncate the destination table before writing. During a recent run, the copy activity failed after the truncation, leaving the destination table empty. You need to prevent data loss in future failures. What should you modify?
medium- A.Add a retry policy to the copy activity.
- B.Enable fault tolerance in the copy activity source.
- ✓ C.Use a staging table and then a stored procedure to swap tables.
- D.Remove the preCopyScript and set writeBatchSize to 0.
Why C: Option C is correct because using a staging table with a stored procedure swap ensures atomicity: if the copy fails, the staging table is discarded and the original table remains intact. Option A is wrong because a retry policy would re-run the entire activity, including the preCopyScript truncation, and would fail again, causing data loss. Option B is wrong because fault tolerance only skips incompatible rows but does not prevent the truncation from occurring; data loss still happens. Option D is wrong because removing the preCopyScript avoids the truncation but setting writeBatchSize to 0 is invalid; even if fixed, without atomicity, a partial write could lead to data loss on failure.
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Last reviewed: Jun 24, 2026
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