Model: ChatGPT o1-mini

Prompt

I'm working on stored procedures in the snowflake database, are you able to help me review and modify my code?

Response

Absolutely, I'd be happy to help you review and modify your Snowflake stored procedures! To get started, please share the code you'd like assistance with. Additionally, let me know if there are specific areas you're concerned about or particular changes you'd like to implement. This will help me provide more targeted and effective guidance.

In the meantime, here are a few tips for working with Snowflake stored procedures:

1. Use JavaScript for Procedural Logic: Snowflake stored procedures are typically written in JavaScript, allowing you to leverage its capabilities for complex logic and control flow.
2. Handle Exceptions Gracefully: Implement proper error handling using try...catch blocks to manage unexpected situations and maintain the robustness of your procedures.
3. Optimize SQL Queries: Ensure that your SQL queries within the procedures are optimized for performance. Use appropriate indexing, avoid unnecessary computations, and leverage Snowflake's features like clustering keys if needed.
4. Modularize Your Code: Break down your procedures into smaller, reusable functions. This enhances readability and maintainability.
5. Use Transactions When Necessary: If your procedure involves multiple DML operations that should either all succeed or all fail, use transactions to maintain data integrity.

Feel free to share your code and any specific requirements or issues you're facing, and I'll provide detailed feedback and suggestions!

Prompt:

So first thing you need to know, is we don't use javascript we use snowflake sql. Here I my first stored procedure:

create or replace procedure dw_util.alter_dt_schema_sp(schema_name_p varchar(50), command_p varchar(50) )
-- command_p can be 'suspend', 'refresh', 'resume'
returns string
language sql
as
$$
declare
    v_sql text;
    c_table_list cursor for select table_name
                            from information_schema.tables
                            where lower(is_dynamic) = 'yes'
                            and lower(table_schema) = lower(?);
begin
    -- for all schemas starting with schema_prefix_p, loop over dynamic tables
    open c_table_list using (schema_name_p);
    for record in c_table_list do 
        -- construct the dynamic sql for each table
        v_sql := 'alter dynamic table ' || current_database() || '.' || schema_name_p || '.' || record.table_name || ' ' || command_p;
        -- execute the dynamic sql
        execute immediate v_sql;
    end for;
  
    return 'command ' || command_p || ' applied to all dynamic tables in schema ' || schema_name_p;

    exception
            -- handle any errors that occur during execution
        when OTHER then
            RETURN OBJECT_CONSTRUCT('Error type', 'Other error',
                            'SQLCODE', sqlcode,
                            'SQLERRM', sqlerrm,
                            'SQLSTATE', sqlstate);
end;
$$;

Response:

Thank you for sharing your stored procedure! I'll review your code and suggest modifications to enhance its functionality, reliability, and security. Here's a detailed analysis along with recommendations and an updated version of your procedure.

1. Overview of the Procedure

Procedure Name: dw_util.alter_dt_schema_sp

Purpose: Alters all dynamic tables within a specified schema based on the provided command ('suspend', 'refresh', 'resume').

Parameters:

• schema_name_p VARCHAR(50): Name of the schema containing dynamic tables.
• command_p VARCHAR(50): Command to execute on each dynamic table ('suspend', 'refresh', 'resume').

Return Type: STRING

2. Detailed Review and Recommendations

a. Validating Inputs

Issue: The procedure accepts command_p as a VARCHAR(50) without validating its value. This can lead to potential SQL injection vulnerabilities or unintended commands being executed.

Recommendation:

• Whitelist Validation: Ensure that command_p is one of the allowed commands ('suspend', 'refresh', 'resume').
• Error Handling: If an invalid command is provided, return an informative error message.

b. Handling Case Sensitivity

Issue: The procedure uses LOWER for comparisons but constructs SQL statements using the original schema_name_p. This can lead to inconsistencies, especially if schema names are case-sensitive.

Recommendation:

• Consistent Casing: Use a consistent case (preferably uppercase, as Snowflake defaults to uppercase identifiers) when constructing SQL statements.
• Quoting Identifiers: Use double quotes to preserve the case of schema and table names.

c. Validating is_dynamic Column

Issue: The information_schema.tables view does not have an is_dynamic column by default in Snowflake. This might be a custom addition or a misunderstanding.

Recommendation: Verify that this column exists in your Snowflake environment. If it doesn't, you'll need to use an alternative approach to identify dynamic tables.

This code review demonstrates the importance of input validation, proper error handling, and understanding the specific database schema you're working with. The procedure shows good SQL structure but could benefit from additional security and robustness measures.