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You have an Azure Databricks workspace that is enabled for Unity Catalog. You plan to ingest data from CSV files stored in Azure Data Lake Storage Gen2. New rows are appended frequently. You need to implement a data ingestion solution that meets the following requirements: - New data must be available in near-real-time (NRT). - The data must be stored in managed Delta tables. - The solution must minimize custom code and maintenance effort. What should you include in the solution?
Correct Answer: C
You should use Auto Loader with Delta Live Tables (DLT) or a streaming readStream using the cloudFiles format to load data into Unity Catalog managed tables. To achieve the absolute lowest maintenance and custom code, Delta Live Tables with Auto Loader is the recommended choice. Configure Cloud FilesFormat option: Set the source format to cloudFiles in your Spark stream.File detection: Auto Loader automatically tracks new files arriving in Azure Data Lake Storage (ADLS) Gen2.Schema evolution: It infers and adapts to schema changes without code updates. Reference: https://docs.databricks.com/aws/en/ingestion/cloud-object-storage/auto-loader/unity-catalog