Design and implement data storage →mediumMultiple ChoiceObjective-mapped

DP-203 Design and implement data storage Practice Question

Exhibit

Refer to the exhibit.

```json
{
  "data": [
    {
      "name": "order_data",
      "path": "orders/*.parquet",
      "partitionBy": ["year", "month", "day"],
      "format": "parquet",
      "options": {
        "compression": "snappy"
      }
    }
  ],
  "source": {
    "provider": "AzureDataLakeStorage",
    "connectionString": "DefaultEndpointsProtocol=https;AccountName=storagedatalake;AccountKey=...;EndpointSuffix=core.windows.net",
    "container": "data"
  },
  "sink": {
    "provider": "AzureSynapseAnalytics",
    "table": "dbo.orders",
    "staging": {
      "linkedServiceName": "AzureDataLakeStorage",
      "folderPath": "staging"
    }
  },
  "copyBehavior": "MergeFiles",
  "faultTolerance": {
    "skipIncompatibleFiles": true,
    "skipIncompatibleRows": true
  }
}
```

You are reviewing a copy job configuration in Azure Data Factory that copies Parquet files from Azure Data Lake Storage Gen2 to Azure Synapse Analytics. The exhibit shows the job settings. If the source folder contains a file that is not in Parquet format (e.g., a CSV file), what will happen?

⚠ Common exam trap

Many exam-takers assume ADF will attempt to read all files in a folder regardless of extension, leading them to choose Option D (corrupt data) or Option B (failure), when in fact ADF respects the file pattern filter and silently skips non-matching files.

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 copy job will skip the CSV file and continue copying other Parquet files.

When using Azure Data Factory's Copy Activity with a wildcard file path or a dataset that filters for Parquet files (e.g., *.parquet), the service evaluates the file pattern before attempting to read the file. If a CSV file is present in the same folder but does not match the Parquet filter, ADF simply ignores it and continues processing only the matching Parquet files. This behavior is by design to allow flexible file selection without causing failures.

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 copy job will skip the CSV file and stop.
Why it's wrong here
It continues with other files.
✗
The copy job will fail with an error.
Why it's wrong here
skipIncompatibleFiles is true, so it skips.
✓
The copy job will skip the CSV file and continue copying other Parquet files.
Why this is correct
skipIncompatibleFiles=true causes skipping non-Parquet files.
✗
The copy job will attempt to read the CSV file as Parquet and may produce corrupt data.
Why it's wrong here
It skips incompatible files entirely.

Go deeper

DP-203 Design and implement data storage Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question