DP-203 Develop data processing Practice Question
Exhibit
{
"type": "Microsoft.DataFactory/factories/pipelines",
"properties": {
"activities": [
{
"name": "CopyData",
"type": "Copy",
"policy": {
"retry": 2,
"timeout": "0:10:00"
},
"inputs": [
{
"referenceName": "DelimitedTextInput",
"type": "DatasetReference"
}
],
"outputs": [
{
"referenceName": "ParquetOutput",
"type": "DatasetReference"
}
],
"typeProperties": {
"source": {
"type": "DelimitedTextSource",
"storeSettings": {
"type": "AzureBlobStorageReadSettings",
"recursive": true
}
},
"sink": {
"type": "ParquetSink",
"storeSettings": {
"type": "AzureBlobFSWriteSettings"
},
"formatSettings": {
"type": "ParquetWriteSettings"
}
},
"translator": {
"type": "TabularTranslator",
"mappings": [
{
"source": {
"name": "Name",
"type": "String"
},
"sink": {
"name": "FullName",
"type": "String"
}
}
]
}
}
}
]
}
}Refer to the exhibit. The pipeline fails with a 'Type mismatch' error. The source file has a column 'Name' of type String, and the destination table expects 'FullName' of type String. What is the most likely cause of the failure?
⚠ Common exam trap
Candidates often assume 'Type mismatch' always refers to incompatible data types (e.g., String vs. Int), when in fact it can also be triggered by a missing source column that the pipeline expects to map, causing a schema-level mismatch.
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 source file does not contain a column named 'Name'.
The pipeline fails with a 'Type mismatch' error because the source file does not contain a column named 'Name'. When the source dataset is configured to read a 'Name' column but the actual file lacks that column, Azure Data Factory or Synapse Pipelines cannot map it to the sink column 'FullName', resulting in a type mismatch error. The error message is misleading because the mismatch is not about data types but about missing source columns, which the service treats as a type incompatibility.
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 recursive setting on the source store is causing duplicate reads.
Why it's wrong here
Recursive=true reads subfolders, but that would not cause a type mismatch error.
- ✓
The source file does not contain a column named 'Name'.
Why this is correct
The column mapping references a source column 'Name', but if the actual file has a different column header, the copy activity fails with type mismatch.
- ✗
The source file has leading/trailing whitespace in the column names.
Why it's wrong here
Whitespace in column names would cause a column not found error, not a type mismatch.
- ✗
The sink column 'FullName' is expecting a different data type than String.
Why it's wrong here
Both are defined as String, so no type mismatch there.
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