A Snowflake Native App provider is using a Snowpark Python UDF to process data before writing it to an event table for consumption by consumer applications. The UDF fails intermittently with a 'Java heap space' error. Which of the following strategies are MOST effective in mitigating this error?

• A. Switch to a Java UDF instead of a Python UDF, as Java UDFs inherently have better memory management in Snowflake.
• B. Implement batch processing within the UDF to process data in smaller chunks, reducing the memory footprint at any given time.
• C. Optimize the Python UDF code to use more memory-efficient data structures and algorithms, reducing overall memory consumption.
• D. Increase the warehouse size used by the consumer application instance, as this controls the memory available to the UDF during event processing.
• E. Configure the event table function to use a larger warehouse size using the EXECUTE AS OWNER clause.

You are deploying a containerized application within a Snowflake Native App using Snowpark Container Services (SPCS). This application needs to interact with Snowflake's metadata, specifically retrieving information about tables and views within the customer's account. Which of the following methods is the MOST appropriate and secure way to achieve this?

• A. Using the 'snowflake-jdbc' driver directly within the container, configured with the customer's Snowflake account credentials, which are passed as environment variables.
• B. Creating a REST endpoint within the container that accepts SQL queries as input and executes them against Snowflake using the application's internal service account, then returns the results as JSON.
• C. Using the Snowflake CLI (snowsql) within the container, configured with the application's service account credentials, to execute queries against the INFORMATION SCHEMA.
• D. Exposing a Snowflake UDF as an API endpoint that the container can call to retrieve metadata. The UDF executes the SQL queries against the INFORMATION SCHEMA.
• E. Leveraging the Snowpark Python API within the container to execute SQL queries against the Snowflake INFORMATION_SCHEMA views.

A data science company is developing a Snowflake Native App that provides advanced fraud detection for financial institutions. The app requires secure access to sensitive transaction data within the consumer's Snowflake account. Which of the following approaches BEST aligns with Snowflake's recommended practices for managing data access and securing data within a Native App?

• A. The app should directly access tables containing transaction data using the consumer's own service account credentials, which are securely stored within the app's code.
• B. The app should directly access transaction data through data sharing from provider account.
• C. The app should use secure views created by the consumer that grant the app read-only access to only the specific transaction data needed for fraud detection.
• D. The app should create and manage its own temporary tables in the consumer account and load transaction data into them for processing.
• E. The app should request full ACCOUNTADMIN privileges in the consumer account to access all necessary data for fraud detection.

You're developing a Snowflake Native App. Part of your application logic involves using a UDF (User-Defined Function) to perform complex calculations on data residing in a table within the consumer's Snowflake account. Which of the following statements correctly describes how you would package and deploy this UDF within your Native App using the application package?

• A. You must create the UDF within a schema in your application package, and grant USAGE privilege on the schema to the application role. The application code can then execute the UDF without any further privilege grants within the consumer account, and the UDF can be called from SQL or other UDFs using unqualified names.
• B. The UDF definition must be created directly within the consumer's account after the application is installed, as UDFs cannot be included in the application package.
• C. You must create the UDF within a schema in your application package, and grant USAGE privilege on the schema to the application role. The consumer will automatically be granted EXECUTE privilege on the UDF.
• D. The UDF definition must be created as an external function, pointing to an external API endpoint that your application controls, enabling the UDF logic to be executed outside of the consumer's Snowflake environment.
• E. You must create the UDF within a schema in your application package. No additional privileges need to be granted, as the application role automatically has all necessary privileges within the application's namespace.

When designing the architecture of a Snowflake Native App, which of the following architectural considerations and trade-offs should you carefully evaluate to optimize performance, security, and cost-effectiveness? (Select all that apply)

• A. Storing all application data within the provider account and accessing it directly from the consumer account using data sharing to avoid data duplication.
• B. Using secured API integration to call the external APIs to get real time details in the app to make the app more useful.
• C. Minimizing data transfer between the provider and consumer accounts by leveraging Snowpark and UDFs for data processing within the consumer's environment.
• D. Choosing the appropriate data access model (e.g., UDFs, stored procedures, Snowpark) based on the specific use case and performance requirements, considering the overhead associated with each approach.
• E. Implementing robust error handling and logging mechanisms to facilitate debugging and monitoring of the application's behavior in both the provider and consumer environments.