hardMultiple ChoiceObjective-mapped
DP-203 Practice Question: A multinational corporation uses Azure Data Lake…
A multinational corporation uses Azure Data Lake Storage Gen2 to store petabytes of parquet files partitioned by date and hour. Data scientists report that queries on the last 7 days of data take over 30 minutes, while queries on older data are fast. The storage account uses the default Azure Blob Storage hierarchical namespace. Which action will MOST improve query performance on recent data?
⚠ Common exam trap
Test-takers frequently confuse partition layout optimization with data format or clustering techniques, overlooking that the hierarchical namespace in ADLS Gen2 makes directory-level partition pruning the most impactful lever for time-range queries.
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
✓
Optimize the partition layout by partitioning by date first, then by hour, to reduce the number of partitions scanned for recent data
Partitioning by date first, then by hour, ensures that queries filtering on the last 7 days scan only the relevant date partitions, drastically reducing the amount of data read. In Azure Data Lake Storage Gen2, the hierarchical namespace allows partition pruning at the directory level, so a date-first layout minimizes the number of partitions scanned for recent data, directly addressing the performance bottleneck.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert the parquet files to CSV format to reduce metadata overhead
Why it's wrong here
CSV is less efficient than parquet for analytical queries.
- ✗
Enable soft delete on the storage account to reduce read latency
Why it's wrong here
Soft delete does not affect read performance.
- ✓
Optimize the partition layout by partitioning by date first, then by hour, to reduce the number of partitions scanned for recent data
Why this is correct
Recent data queries scan fewer partitions, improving performance.
- ✗
Apply Z-order clustering on the parquet files using Azure Databricks
Why it's wrong here
Z-order improves within-file skipping, but the issue is partition pruning.
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
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.