You are working with a Snowflake Notebook and need to execute a series of SQL statements that include both DDL (Data Definition Language) and DML (Data Manipulation Language) operations. You want to e

Question

Options

• AWrap the SQL statements within a 'BEGIN' and 'END' block within the cell. Snowflake Notebooks
• BUse the 'snowflake.connector' Python library to explicitly manage transactions using , followed by
• CPrefix each SQL statement with 'TRY and include a 'CATCH' block at the end to handle any
• DSnowflake Notebooks do not support transactions within a single cell. Each SQL statement is
• ECreate a stored procedure that encapsulates all SQL statements and then call the stored

• A
  6% (2)
• B
  6% (2)
• D
  3% (1)
• E
  84% (26)

Explanation

Rolling back a mixed DDL/DML sequence is fundamentally constrained in Snowflake because DDL statements (CREATE, ALTER, DROP) are auto-committed - they implicitly commit any open transaction and cannot be rolled back. Given this constraint, the most reliable approach is (E) encapsulating all statements in a stored procedure: Snowflake stored procedures support explicit transaction control (BEGIN/COMMIT/ROLLBACK), and while DDL auto-commit behavior still applies internally, the stored procedure pattern provides the best structure for atomic operation grouping and error handling with ROLLBACK in the exception path. Option A is misleading - BEGIN/END blocks in a notebook cell do not override DDL auto-commit behavior. Option B (snowflake.connector transaction management) could partially work for DML but still cannot roll back DDL. Option C is invalid SQL syntax for Snowflake. Option D is factually incorrect - Snowflake does support transactions, just with the DDL auto-commit caveat.

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