When using DataFrames, which type of queries are supported by the Snowflake Spark connector?

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Multiple Choice

When using DataFrames, which type of queries are supported by the Snowflake Spark connector?

Explanation:
The key idea here is that the Snowflake Spark connector for DataFrames is built to fetch data by translating DataFrame read operations into Snowflake SELECT statements and pulling the results into Spark. This path is inherently read-focused, so it supports only SELECT-type queries when you’re reading data into Spark. DML statements (like INSERT, UPDATE, DELETE) and metadata commands (such as SHOW or DESCRIBE) aren’t exposed through the DataFrame interface. If you need to perform those other kinds of SQL actions, you’d use a direct Snowflake connection or separate tooling outside the DataFrame read workflow.

The key idea here is that the Snowflake Spark connector for DataFrames is built to fetch data by translating DataFrame read operations into Snowflake SELECT statements and pulling the results into Spark. This path is inherently read-focused, so it supports only SELECT-type queries when you’re reading data into Spark. DML statements (like INSERT, UPDATE, DELETE) and metadata commands (such as SHOW or DESCRIBE) aren’t exposed through the DataFrame interface. If you need to perform those other kinds of SQL actions, you’d use a direct Snowflake connection or separate tooling outside the DataFrame read workflow.

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