DP-203 Develop data processing Practice Question
You are troubleshooting a slow-running Azure Synapse Pipeline that loads data from Azure Blob Storage into a dedicated SQL pool using a Copy activity. The source is a set of CSV files totaling 500 GB. The sink is a staging table with a clustered columnstore index. The pipeline takes 4 hours to complete. You need to reduce the execution time to under 1 hour. What should you do?
⚠ Common exam trap
Many candidates assume scaling up resources (DIU or DWU) is the universal fix for slow pipelines, but the real bottleneck is the sink write method, and PolyBase is the only option that changes the data loading protocol from row-by-row to bulk parallel loading.
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 PolyBase in the Copy activity sink settings.
Enabling PolyBase in the Copy activity sink settings allows the data to be loaded into the dedicated SQL pool using the high-throughput PolyBase technology, which leverages the SQL pool's distributed architecture and can read data directly from Azure Blob Storage in parallel. This bypasses the bottleneck of row-by-row inserts, drastically reducing load time for large datasets like 500 GB.
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 PolyBase in the Copy activity sink settings.
Why this is correct
PolyBase provides the fastest way to load data into dedicated SQL pool by leveraging its parallel architecture.
- ✗
Increase the Data Integration Units (DIU) in the Copy activity to the maximum.
Why it's wrong here
Increasing DIU improves parallelism but the bottleneck is often the sink; PolyBase is more effective.
- ✗
Increase the dedicated SQL pool's DWU setting to the highest tier.
Why it's wrong here
Scaling up improves query performance but does not change the copy method; the load may still be slow.
- ✗
Partition the staging table on a date column.
Why it's wrong here
Partitioning helps with query performance and partition switching, not with the initial load speed.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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