Which action enables interactive Spark exploration of a file in the lakehouse?

• A. Open a notebook to run Spark interactively.
• B. Switch to the SQL analytics endpoint mode.
• C. Create a Dataflow Gen2.
• D. Publish a dashboard.

Answer: (A)

Interactive Spark exploration is enabled by opening a notebook to run Spark interactively. In a lakehouse environment, a notebook starts a Spark session you can use with PySpark, Scala, or Spark SQL to read the file, transform it, and inspect results step by step. This immediate feedback loop lets you experiment with filters, joins, and aggregations directly on the data.

Switching to the SQL analytics endpoint mode provides a SQL-based interface for querying the lakehouse, which is great for BI tools, but it doesn’t execute Spark code for interactive exploration. Creating a Dataflow Gen2 is about building data pipelines for movement and transformation, not interactive Spark experimentation. Publishing a dashboard is for visualization and sharing results, not for live, code-driven exploration of the data.