Answer: Temporary view

**Explanation:** The correct answer is **Temporary view (D)** because: 1. **Temporary views are session-scoped** - They exist only for the duration of the current Spark session and are automatically dropped when the session ends. 2. **No physical data storage** - Temporary views don't create physical copies of data; they are logical views that reference the underlying tables. 3. **Cost-effective** - Since no data is duplicated or stored separately, storage costs are minimized. 4. **Session isolation** - Other data engineers in other sessions cannot access this temporary view, which aligns with the requirement that it doesn't need to be used by others. **Why other options are incorrect:** - **A. Spark SQL Table**: Creates a physical table that stores data, increasing storage costs. - **B. View**: While views don't store physical data, they are persistent and can be accessed by other sessions/users. - **C. Database**: A container for tables/views, not a relational object that pulls data from tables. - **E. Delta Table**: Creates a physical table with Delta Lake format, storing data and increasing storage costs. **Key points about temporary views:** - Created using `CREATE TEMP VIEW view_name AS query` or `CREATE TEMPORARY VIEW view_name AS query` - Session ends when: opening a new notebook, detaching/reattaching a cluster, installing a Python package, or restarting a cluster - Perfect for intermediate results that don't need persistence or sharing across sessions

Author: Keng Suppaseth