Databricks-DE-Pro Data Ingestion and Acquisition Practice Question
A data engineer is using Databricks Auto Loader to ingest CSV files into a Delta table. The engineer notices that some files have a different delimiter (semicolon instead of comma). Which option should be used to handle this variation?
⚠ Common exam trap
The trap here is assuming Auto Loader can automatically detect and handle different delimiters, but it requires a consistent delimiter across all 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
✓
Preprocess the files to standardize the delimiter before ingestion.
The correct approach is to preprocess the files to standardize the delimiter before ingestion. Auto Loader does not support per-file delimiter detection; it requires a consistent format. By converting all files to a common delimiter, you ensure that Auto Loader parses them correctly and ingests data without errors. This is a common preprocessing step in data pipelines.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the cloudFiles.schemaEvolutionMode to 'addNewColumns' to handle delimiter changes.
Why it's wrong here
Schema evolution mode deals with schema changes like new columns, not delimiter variations. Delimiter is a parsing option, not part of the schema. This setting would not address the delimiter issue and could lead to incorrect parsing or failures.
- ✗
Use the cloudFiles.format option with a custom delimiter per file.
Why it's wrong here
Auto Loader does not support specifying different delimiters per file dynamically. The cloudFiles.format option specifies the file format (e.g., 'csv'), but delimiter is a separate option. You cannot set per-file delimiters in Auto Loader; it expects a consistent format across files.
- ✗
Set the delimiter option to ';' for all files.
Why it's wrong here
Setting a single delimiter for all files would incorrectly parse files that use a comma delimiter. This approach does not handle variation; it would break ingestion for files with the other delimiter. The engineer needs a way to handle both delimiters dynamically or standardize the files before ingestion.
- ✓
Preprocess the files to standardize the delimiter before ingestion.
Why this is correct
Preprocessing the files to use a consistent delimiter (e.g., comma) is the most reliable approach. Auto Loader expects a uniform format; by standardizing delimiters, you ensure correct parsing. This can be done with a separate job or using a Databricks notebook to rewrite files. It avoids ingestion failures and data corruption.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Pro practice question is part of Courseiva's free Databricks 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 Databricks-DE-Pro exam.