You want to use Apache Spark to interactively explore data in a file in the lakehouse. What should you do?

• A. Switch to the SQL analytics endpoint mode
• B. Create a Dataflow Gen2
• C. Use a Data Pipeline
• D. Create a notebook

Answer: (D)

Interactive exploration with Apache Spark in a lakehouse is best done by creating a notebook. A notebook provides an interactive Spark session where you can load data from the lakehouse, run Spark transformations and Spark SQL on the fly, and immediately view results and iterate on ideas. This setup lets you quickly inspect schemas, sample data, perform ad-hoc queries, and visualize findings without committing to a scheduled job or a separate ETL pipeline. Other options are focused on SQL endpoints, orchestration, or batch processing, which don’t offer the same hands-on, iterative coding environment for Spark that a notebook provides.