Snowflake SnowPro Specialty - Native Apps 認定 NAS-C01 試験問題:

1. You're developing a Snowflake Native Application and want to control access to different features based on roles. You have a Streamlit application that displays sensitive data, and you only want users with the 'DATA ANALYST and 'ADMIN' roles to be able to view this dat a. Which of the following methods or a combination of methods are MOST appropriate for enforcing this role-based access control within your Streamlit application and the underlying Snowflake resources?

A) Implement row-level security (RLS) policies on the underlying tables to filter data based on the user's role. Then, within the Streamlit application, simply display the data without any explicit role checks. The RLS policies will automatically ensure that users only see the data they are authorized to see. Grant 'SELECT privilege on the underlying data tables to the 'DATA ANALYST and 'ADMIN' roles directly.
B) Within the Streamlit application, use the function to check for a URL parameter containing the user's role. If the role matches or 'ADMIN', display the data; otherwise, display an error message. Grant 'SELECT' privilege on the underlying data tables to the DATA ANALYST and 'ADMIN' roles directly.
C) Create a custom python module that checks if the user's role matches "DATA_ANALYST or 'ADMIN' and configure it for role based access control.
D) Create a stored procedure that checks the user's role using 'CURRENT and returns the requested data only if the role matches or ' ADMIN'. Call this stored procedure from your Streamlit application. Do not grant any direct privileges on the underlying tables to the 'DATA_ANALYST or 'ADMIN' roles. Set the 'EXECUTE AS CALLER property on the stored procedure.
E) Within the Streamlit application, use 'snowflake.connector' to execute 'SELECT and check if the returned role matches DATA ANALYST or 'ADMIN'. If so, display the data; otherwise, display an error message. Grant USAGE' privilege on a custom role, and grant 'SELECT on the underlying tables and USAGE on the schema to that custom role. Finally grant the 'DATA_ANALYST and 'ADMIN' roles to this custom role.

2. A Native App provider wants to implement comprehensive monitoring of their application's behavior within consumer accounts. They decide to use Event Tables to capture various application events. Which of the following strategies is the MOST appropriate for designing and managing Event Tables for this purpose? Select ALL that apply.

A) Create a single, generic Event Table with a VARIANT column for event-specific data to accommodate all event types.
B) Create separate Event Tables for each distinct event type, with columns tailored to the specific data associated with each event.
C) Implement a data retention policy to automatically purge older events from the Event Tables, minimizing storage costs and improving query performance.
D) Use a centralized Event Table that is shared across all consumer accounts to simplify data aggregation and analysis.
E) Utilize dynamic table creation based on the type of event being recorded, ensuring optimal storage and query performance for each event type. Dynamic table creation is managed programmatically.

3. You are developing a Snowflake Native Application that relies on external functions (UDFs/UDTFs) for data processing. A new version of your application includes significant changes to these external functions, potentially affecting existing consumer data and queries. How should you manage the upgrade process to minimize disruption and ensure data integrity in consumer accounts? Assume consumers rely on your function names in their queries. Which of the following approach is MOST suitable?

A) Use release directives to direct users to an intermediate version that provides a compatibility layer for the external function changes. This layer translates calls to the old function names into calls to the new functions, allowing for a phased transition.
B) Rename all the external functions in the new version and instruct consumers to update their queries accordingly after the upgrade.
C) Update the external functions in place with the new logic. Snowflake's versioning will automatically handle any compatibility issues for existing queries.
D) Create new versions of the external functions with different names while maintaining the old functions in the new version. Consumers can then migrate to the new functions at their own pace. Use release directives to route new users to new functions.
E) Develop wrapper functions in the new version that call the original external functions with the new logic applied. Consumers can then gradually migrate to the wrapper functions without immediately changing their queries.

4. You are developing a Snowflake Native App using Python that performs complex data transformations using UDFs and external functions. During consumer testing, you observe intermittent 'Remote service timed out' errors when calling the external function. The external function is hosted on AWS Lambd a. Which combination of the following actions would BEST address this issue, ensuring reliability without compromising security?

A) Increase the timeout setting for the external function in Snowflake, optimize the Lambda function code for faster execution, and monitor Lambda function metrics (e.g., duration, errors) using CloudWatch. Also, increase the memory allocation for the AWS Lambda function.
B) Cache the results of the external function calls in a Snowflake table to reduce the number of calls to the external service, and implement robust error handling and logging in both the Snowflake UDF and the Lambda function. Always return a value, even in case of error.
C) Migrate the external function to a Snowflake Java UDF to minimize network latency, and reduce the payload size sent to the external function. Verify that the AWS Lambda function and Snowflake instance are in the same region.
D) Implement retry logic in the Python code calling the external function with exponential backoff, and configure Snowflake to use a larger warehouse size to improve network bandwidth. Furthermore, check if AWS Lambda throttles the execution of requests.
E) Implement queue-based processing for external function calls using Snowflake streams and tasks, leverage a message queue service (e.g., SQS) to buffer requests, and ensure the Lambda function has sufficient concurrency and is not being throttled.

5. You are designing a Snowflake Native Application that processes customer dat a. To comply with data residency requirements, you need to ensure that the application logic runs within the customer's Snowflake account, but the application code is owned and managed by your organization. Which of the following approaches BEST achieves this requirement while providing version control and updates?

A) Build the application logic as a set of stored procedures and UDFs within the application package. Provide a setup script that creates these objects in the customer's account during installation.
B) Embedd the raw application code directly into the SETUP script so that it gets re-deployed on every run.
C) Create a Docker container containing the application logic and deploy it as a Snowflake External Function. Share the container image with customers and instruct them to deploy it in their environment.
D) Use Snowflake's Data Sharing feature to directly share the database and schema containing the application logic with customers. Grant them ownership of these objects.
E) Develop the application using Snowflake's Snowpark API and package the compiled code within the application package. The setup script will execute the Snowpark code within the customer's Snowflake account.

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