Version 2.2.0+ of the Snowflake Spark Connector uses a default staging for data exchange.

• A. Temporary Snowflake internal stage
• B. Amazon S3 bucket
• C. Azure Blob storage container
• D. Local storage

Answer: (A)

The concept being tested is how data is staged when moving data from Spark into Snowflake using the Spark Connector. In version 2.2.0 and newer, the connector uses a default staging area that is a temporary Snowflake internal stage. This means Snowflake itself provides and manages the storage location for the data during the transfer, without requiring you to configure external cloud storage or local disks. It streamlines the process, avoids extra credential setup, and the staged data is handled by Snowflake and cleaned up after loading. Using an external storage option like S3 or Azure would require explicit stage configuration and credentials, and staging to local storage isn’t feasible for distributed Spark workloads that need to share data across workers.