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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. You are developing a Snowflake Native Application using Scala for a financial institution. The application processes sensitive transaction dat a. During consumer-side testing, the consumer reports intermittent 'java.lang.NullPointerException' errors. You suspect the issue lies within your UDE How can you effectively trace and debug this issue, considering data privacy requirements and without directly exposing sensitive consumer data in your logs?

A) Implement a custom error handling mechanism in Scala that catches 'NullPointerException', logs a generic error message with a unique error code to the event table, and then re-throws a more descriptive exception to the consumer. The consumer can then report the error code to the provider for further investigation. The provider can analyze the code, without actual consumer sensitive data.
B) Rely solely on Snowflake's query history to identify failing queries. Analyze the input data and execution plan to infer the cause of the NullPointerException.
C) Implement structured logging within the Scala UDF using SLF4J and Logback. Include contextual information (e.g., transaction IDs, timestamps) at various stages of the UDF execution. Use Snowflake's masking policies on the event table to protect sensitive data during logging. This is the best method as it's the more granular and effective
D) Utilize 'System.out.println' statements within the Scala UDF to print debug messages directly to the query result. The consumer can view these messages to identify the source of the error, with the provider having no visibility.
E) Use Snowflake's event table to capture all exceptions, filtering for the UDF name. Redact potentially sensitive fields in the logs after extraction using a Python script executed on the provider side.

2. You're developing a Snowflake Native Application that requires frequent updates to its core logic. You need to implement a deployment strategy that minimizes downtime and allows for easy rollback in case of issues. Which combination of deployment techniques would BEST achieve this goal when deploying updates to your Snowflake Native App? (Choose two)

A) Use the ALTER APPLICATION' command with the 'FORCE option to immediately replace the existing application with the new version, ignoring any potential compatibility issues.
B) Deploy the updated application directly to the production environment during off-peak hours, relying on thorough testing in a pre-production environment to minimize risks.
C) Implement a blue/green deployment strategy, maintaining two identical environments. Deploy the update to the 'blue' environment, test, and then switch traffic from 'green' to 'blue'. If issues arise, switch back to 'green'.
D) Implement canary deployments by gradually rolling out the new version to a small subset of consumers, monitoring performance, and then expanding the rollout if no issues are detected.
E) Utilize zero-copy cloning to create a staging environment of your application, deploy the new version to the clone, and then swap the clone with the production environment for near-instant deployment.

3. Consider a scenario where you are developing a Snowflake Native App which utilizes a UDF (User-Defined Function). This UDF needs to access a secure external API using a secret stored securely within Snowflake. Which of the following statements are accurate regarding the necessary privileges and architecture for this setup? (Select all that apply)

A) The application instance must be granted the REFERENCE USAGE privilege on the secret to allow the UDF to access it.
B) The application package needs the EXECUTE privilege on the secret for the UDF to use it.
C) The application developer needs the "APPLY privilege to create the secret in the application package.
D) The consumer account automatically inherits access to secrets created in the application package.
E) The application developer needs the 'CREATE SECRET privilege to create the secret in the application package.

4. You are developing a Snowflake Native Application that manages customer accounts. In version 1.0, you had a table named 'CUSTOMER_ACCOUNTS with columns 'ACCOUNT D', 'CUSTOMER NAME, and 'EMAIL'. You are now releasing version 2.0, which requires adding a new column 'PHONE NUMBER to the 'CUSTOMER ACCOUNTS table, but you need to ensure backward compatibility and allow seamless upgrades for existing installations. Which of the following approaches within the 'setup.sqr file is the MOST robust and reliable to implement this schema change without disrupting existing users?

A)

B)

C)

D)

E)

5. 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) Minimizing data transfer between the provider and consumer accounts by leveraging Snowpark and UDFs for data processing within the consumer's environment.
B) Implementing robust error handling and logging mechanisms to facilitate debugging and monitoring of the application's behavior in both the provider and consumer environments.
C) 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.
D) Using secured API integration to call the external APIs to get real time details in the app to make the app more useful.
E) Storing all application data within the provider account and accessing it directly from the consumer account using data sharing to avoid data duplication.

Solutions: