DP-203 Develop data processing Practice Question
You are optimizing a pipeline in Azure Data Factory that copies data from Azure Blob Storage to Azure Synapse Analytics. The pipeline uses a copy activity with PolyBase. The data is partitioned by date in Blob Storage. You notice that the load is slow. What is the most likely cause?
⚠ Common exam trap
The trap here is that candidates often focus on file format (Parquet vs. CSV) or storage type (Blob vs. ADLS Gen2) as the primary performance factor, when in reality the number and size of files is a more common and impactful bottleneck in PolyBase loads.
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 source files are too many and too small (e.g., thousands of 1 MB files)
PolyBase in Azure Synapse Analytics performs best when reading large, contiguous files. When the source contains thousands of small files (e.g., 1 MB each), PolyBase must initiate a separate read operation for each file, causing excessive overhead from file open/close operations and metadata requests. This dramatically reduces throughput compared to reading fewer, larger files.
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 source files are stored in Azure Blob Storage instead of Data Lake Storage Gen2
Why it's wrong here
PolyBase reads from Blob Storage without requiring Data Lake Storage Gen2; the hierarchical namespace is not a prerequisite for the copy activity. It is tempting because Gen2 is recommended for analytics workloads, yet the stem's partitioning and PolyBase setup already work over Blob, so storage account type is not the cause.
- ✗
The source files are in CSV format instead of Parquet
Why it's wrong here
PolyBase reads CSV through row-based parsing, so columnar compression and predicate pushdown are unavailable, slowing the load. CSV is tempting for compatibility with legacy exports, but Parquet would let PolyBase read columnar data directly, which is the correct choice when source format is the bottleneck.
- ✓
The source files are too many and too small (e.g., thousands of 1 MB files)
Why this is correct
PolyBase reads many small files inefficiently because each file incurs separate metadata and open/close overhead, and parallelism is limited by file count rather than volume. Thousands of 1 MB files therefore throttle throughput, making file granularity—not total data size—the bottleneck in this Blob Storage to Synapse copy.
- ✗
The sink table has a clustered columnstore index
Why it's wrong here
A clustered columnstore index accelerates PolyBase loads into Synapse dedicated SQL pools by enabling efficient bulk compression and minimal logging. It is tempting to blame indexing for write overhead, but columnstore is the recommended target for this pattern, so it is not the cause of slowness.
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 |
Go deeper
Related to this question
Learn chapter
Implement Azure Data Factory Pipelines
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.