Snowflake SPS-C01 - Snowflake Certified SnowPro Specialty - Snowpark

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Snowflake SPS-C01 Exam Syllabus Topics:

Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You have a SQL query stored in a file named 'query.sqr which contains several complex analytical calculations. The query depends on a Snowpark 'session' object already established. You want to create a Snowpark DataFrame from the result of this query. Which of the following code snippets achieves this with optimal performance and readability, assuming correct file access permissions?

A)

B)

C)

D)

E)

2. A data engineer is tasked with creating a Snowpark Python application that needs to access data from multiple Snowflake accounts and regions. All accounts are using Snowflake's Business Critical edition. Which of the following approaches would be the MOST efficient and maintainable for managing and switching between different Snowpark sessions in this scenario?

A) Create separate Python scripts for each account and region, hardcoding the account identifiers and credentials within each script.
B) Create a new Anaconda environment for each Snowflake account and install the necessary packages in each environment.
C) Create a configuration file (e.g., YAML or JSON) that stores the account identifiers and other connection details for each Snowflake account and region. Load this configuration and create separate Snowpark session objects for each account, storing them in a dictionary or list.
D) Use a single Snowpark session object and dynamically update the connection parameters (account identifier, username, password) whenever switching to a different account and region.
E) Use the 'snowflake.connector.connect' method to directly establish connections without using the Snowpark Session object.

3. You have a Python function that takes a string as input and returns a sentiment score (a float between -1 and 1). This function relies on a large pre-trained Natural Language Processing (NLP) model. You want to deploy this function as a UDF in Snowpark and optimize its performance, specifically minimizing the model loading time for each execution. You have already uploaded the model to a stage named '@my_stage/models'. Select the option that combines caching techniques and UDF deployment strategies to achieve the best performance.

A)

B) Option B and C are best and gives a scalable solution
C)

D)

E)

4. Consider the following Snowpark code snippet that defines and registers a UDF:

Which of the following statements about this code are TRUE?

A) The default value of 'salutation' in the Python function will be used even when calling the UDF from SQL if the salutation parameter is omitted.
B) The 'replace=True' argument ensures that any existing UDF with the same name ('ADD_SALUTATION') is overwritten.
C) The UDF is registered as a permanent UDF and stored in the specified stage for future use.
D) The UDF is registered as a temporary UDF and will be removed when the session ends.
E) The 'input_types' parameter is redundant because Python's type hints are automatically used to determine the input types.

5. You are building a Snowpark Python application to perform complex data transformations and want to leverage external packages not pre-installed in the Snowflake environment. You need to ensure these packages are available within your Snowpark session. Which of the following methods are valid for deploying and using these third-party packages within your Snowpark Python environment? (Select TWO)

A) Utilize Snowflake's Anaconda channel integration and specify the package names as strings in the method. Snowflake will automatically resolve and install the packages from the Anaconda channel.
B) Deploy the required packages using the SnowCLl package management commands, and then the Snowpark session will be able to automatically use the deployed packages.
C) Manually install the packages on the Snowflake compute pool nodes before starting the Snowpark session.
D) Use the 'session.addDependency()' method to upload individual '.py' files containing the package code directly to the Snowflake internal stage.
E) Create a 'conda' environment file ('environment.yml') specifying the required packages and use the method to upload the environment definition. Snowflake will automatically install the packages within the session's environment.

Solutions: