DP-203 Develop data processing Practice Question
Exhibit
{
"type": "Microsoft.Synapse/workspaces/databases/tables",
"properties": {
"source": {
"provider": "ABFS",
"location": "abfss://container@storage.dfs.core.windows.net/data/"
},
"format": {
"type": "parquet",
"derivedModel": false
},
"options": {
"recursive": true
}
}
}Refer to the exhibit. You are creating a serverless SQL table in Azure Synapse Analytics that reads Parquet files from the specified location. The folder contains multiple Parquet files with different schemas. When querying the table, you get an error about schema mismatch. What is the most likely reason?
⚠ Common exam trap
Many exam-takers assume serverless SQL can automatically handle heterogeneous schemas (like Spark does with mergeSchema), but in reality it requires all files to share the exact same schema as the first file it reads.
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 serverless SQL pool infers schema from the first file and expects all files to have the same schema.
Azure Synapse serverless SQL pools infer the schema from the first Parquet file encountered in the specified location. When multiple Parquet files with different schemas exist, the pool expects all subsequent files to match that initial schema. If any file has a different schema (e.g., different column names, data types, or number of columns), a schema mismatch error is raised. This behavior is by design, as serverless SQL does not merge or reconcile disparate schemas across 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 Parquet files are not using the .parquet extension.
Why it's wrong here
The extension is not shown; but if they are Parquet, the extension is not required for inference.
- ✗
The derivedModel option is set to false, which disables schema inference.
Why it's wrong here
derivedModel=false means no model is used; schema is still inferred from files.
- ✓
The serverless SQL pool infers schema from the first file and expects all files to have the same schema.
Why this is correct
Serverless SQL uses schema inference from the first file; subsequent files with different schemas cause errors.
- ✗
The recursive option is causing the table to include files from subfolders that have different schemas.
Why it's wrong here
Recursive only includes subfolders; schema inference still uses the first file.
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
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