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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. You have a Snowflake Native Application listed on the Marketplace. You need to update the application to add a new feature, which requires changes to both the application code and the database schema within the application package. You want to ensure a seamless upgrade experience for existing consumers, minimizing downtime and data loss. What is the MOST appropriate strategy for deploying this update?

A) Create a new version of the application package. Before releasing, use a feature flag system to gradually roll out the new feature to a subset of consumers, monitoring for any issues before a full release.
B) Modify the existing application package directly with the updated code and schema. This will automatically update the application for all consumers.
C) Create a new version of the application package. Implement a Snowpark Python stored procedure within the new version that handles schema migrations and data transformations. This procedure should be automatically executed during the upgrade process.
D) Create a new version of the application package. Include a setup script that detects the existing version of the application and performs any necessary schema migrations or data transformations. Announce the new version and instruct consumers to manually upgrade.
E) Create a new version of the application package with the updated code and schema. Consumers will automatically be upgraded to the new version upon release.

2. You are developing a Snowflake Native App that processes streaming data from a Kafka topic. The app needs to continuously ingest data, perform real-time transformations, and store the results in a Snowflake table within the app's managed database. Which Snowflake feature(s) and approach(es) are BEST suited for implementing this data ingestion and processing pipeline within the Native App?

A) Leverage Snowflake Snowpipe Streaming to ingest data directly from the Kafka topic into the target table, combined with Snowflake Tasks to handle any required data transformations.
B) Employ a combination of Snowflake Snowpipe Streaming for data ingestion and Dynamic Tables for continuous, incremental data transformations within the application's managed database.
C) Use a Snowflake Stream to capture changes in the Kafka topic and then use a Snowflake Task to periodically merge these changes into the target table.
D) Implement a custom Kafka consumer within a Java User-Defined Function (UDF) to read data from the Kafka topic and directly insert it into the target table.
E) Use Snowflake Pipes to continuously ingest data from the Kafka topic into a staging table and then use stored procedures to periodically transform and load the data into the target table.

3. A Native Application provider is developing an application that relies on data residing in a shared database, 'EXTERNAL DATA'. They want to ensure that their application role 'app_role' only has access to specific tables and views within 'EXTERNAL DATA', and they also want to minimize the need for future privilege grants as new tables are added to 'EXTERNAL DATA. Which combination of SQL statements below achieves these goals with the principle of least privilege in mind? Assume all tables are in the PUBLIC schema.

A)

B)

C)

D)

E)

4. You are developing a Snowflake Native Application that utilizes a custom stage for storing large intermediate datasets during processing. Your CI/CD pipeline involves automated testing in a dedicated testing account. To ensure proper isolation and prevent interference with production data, how should you configure the stage path within your application package version definition, considering the stage name might differ between development and test environments?

A) Define the stage path as a parameter in the application installation script. When installing the application in each environment, pass the correct stage path as an argument.
B) Employ a versioned configuration file (e.g., YAML) within the application package. The CI/CD pipeline should replace placeholders in the configuration file with environment-specific stage paths before creating the version.
C) Use a Snowflake Secret to store the stage path and retrieve it dynamically during application installation. The secret's value will be environment-specific.
D) Utilize Snowflake's and 'CURRENT functions in conjunction with conditional logic within the application to derive the stage path based on the environment.
E) Hardcode the stage name and path directly within the setup script of the version. This approach is simple and ensures consistent access across environments.

5. You are preparing to deploy a Snowflake Native Application to the Snowflake Marketplace. You have implemented versioning using the 'VERSION' clause in your setup script. Your application relies on a specific shared data source that is only available in the AWS us- west-2 region. To ensure that consumers in other regions can still install and use your application, you decide to offer different versions with region-specific logic. Which of the following approaches is the MOST effective and recommended to manage region-specific configurations and data sharing across multiple versions of your Snowflake Native Application?

A) Create separate application packages for each region, containing region-specific configurations and data sharing setups. This ensures consumers only install the version relevant to their region.
B) Use the 'PATCH' clause during application deployment to selectively modify the configuration based on the target region. Deploy the same application package to all regions.
C) Implement conditional logic within the application's stored procedures to check the current region and adjust data sharing and execution accordingly using Package all configurations within a single version.
D) Use separate schemas within the application package for each region, and configure application roles with permissions to only access schemas relevant to their region. No changes to code logic are required.
E) Implement a build process that generates region-specific setup scripts based on environment variables using a CI/CD pipeline. Each version of the application will then contain the right setup script based on the target region.

Solutions: