- A
Split the Parquet files into many small files (e.g., 64 MB each) to maximize parallelism.
Why wrong: Many small files increase overhead and can degrade performance.
- B
Convert the Parquet files to CSV format before loading using PolyBase.
Why wrong: CSV is less efficient than Parquet for PolyBase loads.
- C
Use the COPY INTO command to load the Parquet files directly into the dedicated SQL pool.
Why wrong: COPY INTO is optimized for smaller loads; CTAS is better for large-scale loads.
- D
Create an external table pointing to the Parquet files and use CREATE TABLE AS SELECT (CTAS) to load the data.
CTAS with external tables enables predicate pushdown and efficient column pruning.
Question 590 of 851
DP-203 PolyBase Practice Question
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. A key principle to apply: polyBase. 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 designing a data ingestion pipeline for Azure Synapse Analytics using PolyBase. The source data is in Azure Blob Storage, with files in the Parquet format. The data volume is approximately 2 TB daily. You need to minimize the time to load data into a dedicated SQL pool table. Which approach should you recommend?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
✓
Create an external table pointing to the Parquet files and use CREATE TABLE AS SELECT (CTAS) to load the data.
Option D is correct because using CREATE TABLE AS SELECT (CTAS) with an external table pointing to Parquet files leverages PolyBase's massively parallel processing capabilities. While the COPY INTO command does support Parquet format in dedicated SQL pools, CTAS offers superior performance for large-scale daily ingestion (2 TB) as it allows for distribution and index optimizations during the load, and it reads the compressed columnar Parquet data directly, minimizing I/O. CTAS also integrates seamlessly with PolyBase's external table architecture, making it the optimal choice for minimizing load time.
Key principle: PolyBase
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Split the Parquet files into many small files (e.g., 64 MB each) to maximize parallelism.
Why it's wrong here
Many small files increase overhead and can degrade performance.
- ✗
Convert the Parquet files to CSV format before loading using PolyBase.
Why it's wrong here
CSV is less efficient than Parquet for PolyBase loads.
- ✗
Use the COPY INTO command to load the Parquet files directly into the dedicated SQL pool.
Why it's wrong here
COPY INTO is optimized for smaller loads; CTAS is better for large-scale loads.
- ✓
Create an external table pointing to the Parquet files and use CREATE TABLE AS SELECT (CTAS) to load the data.
Why this is correct
CTAS with external tables enables predicate pushdown and efficient column pruning.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
PolyBase
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap is that candidates may assume the COPY INTO command (option C) is the best choice because it is newer and supports Parquet directly. However, for very large data volumes like 2 TB daily, the CREATE TABLE AS SELECT (CTAS) approach with an external table leverages PolyBase's massively parallel architecture more effectively, as it distributes the load across all compute nodes and allows for optimizations during the load (e.g., specifying distribution and indexes). While COPY INTO can also read Parquet in parallel, CTAS typically yields superior performance for bulk ingestion into dedicated SQL pools, making option D the correct recommendation.
Detailed technical explanation
How to think about this question
PolyBase uses a pushdown computation model where the SQL pool's compute nodes read Parquet files directly from Azure Blob Storage via the Hadoop Distributed File System (HDFS) connector, leveraging columnar pruning and predicate filtering at the storage layer. CTAS internally creates a new table with a single transaction, allowing you to specify distribution (e.g., ROUND_ROBIN or HASH) and index type (e.g., CLUSTERED COLUMNSTORE) during the load, which avoids a separate table rebuild. In real-world scenarios, this approach can achieve throughput of several TB per hour, especially when the Parquet files are sized between 256 MB and 1 GB and stored in a separate container to avoid contention.
KKey Concepts to Remember
- PolyBase
- CREATE TABLE AS SELECT (CTAS)
- Parquet
- Massively Parallel Processing (MPP)
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
PolyBase
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.
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.
Review polyBase, then practise related DP-203 questions on the same topic to reinforce the concept.
- →
Develop data processing — study guide chapter
Learn the concepts, then practise the questions
- →
Develop data processing practice questions
Targeted practice on this topic area only
- →
All DP-203 questions
851 questions across all exam domains
- →
Microsoft Azure Data Engineer Associate DP-203 study guide
Full concept coverage aligned to exam objectives
- →
DP-203 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related DP-203 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Secure, monitor, and optimize data storage and data processing practice questions
Practise DP-203 questions linked to Secure, monitor, and optimize data storage and data processing.
Design and develop data processing practice questions
Practise DP-203 questions linked to Design and develop data processing.
Design and implement data security practice questions
Practise DP-203 questions linked to Design and implement data security.
Monitor and optimize data storage and processing practice questions
Practise DP-203 questions linked to Monitor and optimize data storage and processing.
Design and implement data storage practice questions
Practise DP-203 questions linked to Design and implement data storage.
Develop data processing practice questions
Practise DP-203 questions linked to Develop data processing.
DP-203 fundamentals practice questions
Practise DP-203 questions linked to DP-203 fundamentals.
DP-203 scenario practice questions
Practise DP-203 questions linked to DP-203 scenario.
DP-203 troubleshooting practice questions
Practise DP-203 questions linked to DP-203 troubleshooting.
Practice this exam
Start a free DP-203 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — PolyBase.
What is the correct answer to this question?
The correct answer is: Create an external table pointing to the Parquet files and use CREATE TABLE AS SELECT (CTAS) to load the data. — Option D is correct because using CREATE TABLE AS SELECT (CTAS) with an external table pointing to Parquet files leverages PolyBase's massively parallel processing capabilities. While the COPY INTO command does support Parquet format in dedicated SQL pools, CTAS offers superior performance for large-scale daily ingestion (2 TB) as it allows for distribution and index optimizations during the load, and it reads the compressed columnar Parquet data directly, minimizing I/O. CTAS also integrates seamlessly with PolyBase's external table architecture, making it the optimal choice for minimizing load time.
What should I do if I get this DP-203 question wrong?
Review polyBase, then practise related DP-203 questions on the same topic to reinforce the concept.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
PolyBase
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 →
Keep practising
More DP-203 practice questions
- You are designing a data storage solution for IoT sensor data. The data is written thousands of times per second and req…
- A data processing job in Azure Synapse Analytics writes results to a table in the dedicated SQL pool. After a failure, t…
- A multinational corporation uses Azure Data Lake Storage Gen2 to store petabytes of parquet files partitioned by date an…
- A company ingests streaming data from IoT devices into Azure Event Hubs. The data must be processed in near real-time to…
- Which THREE factors should be considered when choosing between Azure Stream Analytics and Azure Databricks for a real-ti…
- You are designing a data lake on Azure Data Lake Storage Gen2. The data will be used by both batch processing (Spark) an…
Last reviewed: Jul 4, 2026
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.