DP-203 Develop data processing Practice Question
You are using Azure Synapse Analytics serverless SQL pool to query Parquet files in Azure Data Lake Storage Gen2. The query returns fewer rows than expected. What should you check first?
⚠ Common exam trap
The trap here is that candidates often jump to schema or permission issues first, but the most frequent cause of missing rows in serverless SQL pool queries is an overly restrictive file path or pattern in the OPENROWSET query.
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
✓
Verify the file path and pattern in the OPENROWSET query.
When using OPENROWSET in Azure Synapse serverless SQL pool to query Parquet files, the most common reason for fewer rows than expected is an incorrect file path or pattern. If the path or pattern is too restrictive (e.g., missing a wildcard or pointing to a subfolder instead of the root), the query will only read a subset of the files, resulting in fewer rows. This is the first thing to verify before investigating schema or permissions issues.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ensure the external table has the correct schema definition.
Why it's wrong here
Serverless SQL pool infers schema from Parquet metadata, so a mismatched external table definition would surface as conversion errors, not silent row loss. Checking the schema is tempting because external tables are the usual suspect for column issues, yet the stem's undercount points to predicate pushdown or file-path filtering instead.
- ✗
Check that the Microsoft Entra ID identity has read permissions on the storage account.
Why it's wrong here
Missing read permissions would cause the query to fail with an authorisation error, not silently return fewer rows. It is tempting because storage access is a common serverless SQL pool issue, but partial results point to schema or file-path handling, such as mismatched columns or unread partitions.
- ✗
Check the compression codec used in the Parquet files.
Why it's wrong here
An unsupported compression codec would raise a query error rather than truncate the row count. It is tempting because codec mismatches do break Parquet reads, but serverless SQL pool either decodes the file or fails outright; fewer rows instead suggests schema inference or partition pruning issues.
- ✓
Verify the file path and pattern in the OPENROWSET query.
Why this is correct
OPENROWSET reads only the files matched by the specified path and wildcard pattern; an incorrect folder, filename or pattern silently omits files, so verifying that location first explains missing rows before investigating schema or format issues.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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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.