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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. You are designing a Snowflake Native App that processes sensitive customer dat a. To comply with data residency requirements, you need to ensure the application processes data exclusively within the consumer's Snowflake account and does not transmit data outside.
Which features of the Snowflake Native App Framework support this requirement? (Select all that apply)

A) Stored Procedures: Allows the application to execute custom logic within the consumer's Snowflake environment, processing data locally.
B) Secure Data Sharing: Allows the application to access data directly within the consumer's account without copying or moving it.
C) Application Packages: Package the entire application including code and configuration, ensuring data locality and not data transfer outside environment
D) External Functions: Enables the application to call external services for data processing and enrichment, ensuring all data remains within the Snowflake environment.
E) Snowflake Marketplace: Provides a secure and governed platform for distributing the application without requiring direct access to the consumer's account.

2. As a Native App Provider, you've identified a performance bottleneck in a query against a table within your application's container due to an inefficient join. The query is part of a view exposed to consumers. Which of the following actions would be MOST effective in improving the query performance while minimizing disruption to consumers?

A) Implement a scheduled task to regularly update the statistics of the table involved in the join. This will help the query optimizer make better decisions, and consumers will see improved performance gradually.
B) Add a 'CLUSTER BY clause to the underlying table based on the join keys. Consumers will automatically benefit from improved query performance without any changes on their end.
C) Create a search optimization policy on columns used in the 'WHERE' clause in the view. This does not require any changes from the consumers.
D) Rewrite the query in the view definition to use a more efficient join algorithm (e.g., using hints). Consumers will automatically benefit from the improved performance.
E) Create a materialized view in place of the existing view, pre-computing the join results. This will require consumers to update their queries to use the new materialized view name.

3. A Snowflake Native App developer wants to utilize a README.md file within their application package. Which of the following statements accurately describe the supported usage and purpose of the README.md file in this context?

A) The README.md file is a Markdown formatted file and used only for internal documentation by the app developer and is not exposed to consumers through any Snowflake interface.
B) The README.md file is automatically displayed to consumers within the Snowflake Marketplace listing, providing a detailed overview of the app's functionality and installation instructions.
C) The README.md file must adhere to a specific Snowflake schema for metadata to be automatically extracted and displayed within the consumer's Snowflake environment post-installation.
D) The README.md file can be programmatically accessed within the application logic using a Snowflake-provided API to dynamically generate documentation for the consumer.
E) Snowflake automatically renders the READMmd file as part of the application s user interface within the consumer s account, allowing them to view documentation directly from Snowflake.

4. A Native App developer is using Snowflake's Event Tables for tracing the execution of their application. They have noticed a significant performance overhead when event logging is enabled, particularly for high-volume UDFs. Which of the following strategies would be MOST effective in mitigating the performance impact of event logging while still capturing valuable tracing information?

A) Increase the frequency of event table flushes to reduce the number of events buffered in memory. This minimizes memory pressure and write latency.
B) Implement sampling or conditional logging within the UDFs, only logging events for a subset of executions or when specific conditions are met. Utilize asynchronous logging techniques where appropriate to offload logging operations.
C) Disable event logging entirely for high-volume UDFs to eliminate the performance overhead.
D) Write event data directly to an external cloud storage system (e.g., AWS S3, Azure Blob Storage) bypassing Snowflake's Event Tables altogether.
E) Reduce the number of columns captured in the event tables to minimize the amount of data being written. Store all tracing data in a single large event table to simplify querying.

5. You're developing a Snowpark Container Services application. Your 'service.yaml' file defines a service named 'data_processor'. You want to create a service endpoint, 'ingest_endpoint' , that is secured and accessible only by authorized consumers of your Snowflake Native Application. Select the TWO SQL statements that, when used together, will correctly create and bind the service endpoint, ensuring proper OAuth authentication and authorization.

A) CREATE SERVICE ENDPOINT ingest_endpoint FOR SERVICE data_processor WITH AUTHENTICATION TYPE = OAUTH;
B) BIND SERVICE ENDPOINT ingest_endpoint FOR SERVICE data_processor WITH AUTHENTICATION TYPE = OAUTH TO APPLICATION PACKAGE;
C) ALTER SERVICE data_processor ADD ENDPOINT ingest_endpoint WITH AUTHENTICATION TYPE = OAUTH;
D) CREATE OR REPLACE SERVICE ENDPOINT ingest_endpoint FOR SERVICE data_processor WITH AUTHENTICATION TYPE = SNOWFLAKE_JWT;
E) BIND SERVICE ENDPOINT ingest_endpoint FOR SERVICE data_processor WITH AUTHENTICATION TYPE = NONE TO APPLICATION PACKAGE;

Solutions: