Databricks-DE-Pro Developing Code (Python/SQL) Practice Question
Which property must be set to ensure a Spark Structured Streaming query can handle changes to the source data schema, such as adding a new column?
⚠ Common exam trap
Candidates often select generic Spark options like 'mergeSchema' which applies to batch processing, instead of the specific Auto Loader configuration required for streaming schema evolution.
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
✓
cloudFiles.schemaEvolutionMode = 'addNewColumns'
The `cloudFiles.schemaEvolutionMode` property allows the Auto Loader to adapt to schema changes automatically. In production streaming environments, this is vital because data sources often evolve over time. Without this, the streaming job would fail when it encounters a record that does not match the schema inferred at the start of the job, resulting in pipeline downtime and manual intervention to reset the state.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
cloudFiles.inferSchema = 'false'
Why it's wrong here
Setting inferSchema to false disables the automatic detection of data types. While this might improve performance by avoiding a scan of the input data, it does not solve the problem of schema evolution. In fact, it forces the engineer to provide a manual schema, making the system less flexible to incoming data changes.
- ✓
cloudFiles.schemaEvolutionMode = 'addNewColumns'
Why this is correct
This specific mode instructs the Auto Loader to detect new columns in incoming data files and update the target table schema automatically. This is the recommended setting for production pipelines where the upstream source schema is expected to grow over time, ensuring continuous operation without manual schema management or pipeline restarts.
- ✗
cloudFiles.maxFilesPerTrigger = 'auto'
Why it's wrong here
This property controls the throughput of the stream, not the schema. It determines how many files the streaming engine should process in each micro-batch. Adjusting this is useful for performance tuning and preventing resource exhaustion, but it has no impact on how the system reacts to changes in the structure of the data records.
- ✗
cloudFiles.useIncrementalListing = 'true'
Why it's wrong here
Incremental listing is an optimization for file discovery, particularly in large storage buckets. It reduces the cost and time of listing files by only looking for new additions. While it is a best practice for efficiency, it does not handle schema changes or structural updates, making it irrelevant to the problem of schema evolution.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
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