DP-203 Develop data processing Practice Question
You need to process a large number of small files (each < 1 MB) from Azure Blob Storage in Azure Synapse Analytics. The processing is I/O-bound due to many small file operations. Which approach should you use to improve performance?
⚠ Common exam trap
Test-takers frequently confuse file format conversion (Avro) or write optimization with read-side partition coalescing, failing to recognize that the core issue is the number of partitions created during file scanning, not the data format or write behavior.
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
✓
Use 'spark.sql.files.maxPartitionBytes' to coalesce small files into larger partitions.
`spark.sql.files.maxPartitionBytes` controls the maximum number of bytes packed into a single partition when reading files. By increasing this value, Spark coalesces many small files into fewer, larger partitions, reducing the overhead of task scheduling and I/O operations. This directly addresses the I/O-bound bottleneck caused by processing numerous small files in Azure Synapse Analytics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use wildcard paths to read multiple files at once.
Why it's wrong here
Wildcard paths still read each file individually.
- ✗
Enable optimized write on the Spark session.
Why it's wrong here
Optimized write improves output performance, not input.
- ✗
Convert the files to a binary format like Avro before processing.
Why it's wrong here
Changing format does not reduce the number of small files.
- ✓
Use 'spark.sql.files.maxPartitionBytes' to coalesce small files into larger partitions.
Why this is correct
This configuration merges small files into larger partitions, reducing overhead.
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 |
Go deeper
Related to this question
About these practice questions
One of 760 original DP-203 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.