Free Access Snowflake.SPS-C01.v2026-07-23.q130 Practice Test (Page 22)

Question 101

You are developing a Snowpark application using Visual Studio Code and the Snowflake VS Code extension. You want to configure the extension to automatically detect and use a specific Anaconda environment for your Snowpark development. Assuming you have already created an Anaconda environment named 'snowpark_env', which configuration setting in the VS Code settings.json file would correctly specify the Python path for the Snowflake extension?

A."snowflake.snowpark.pythonPath": "Ipath/to/anaconda3/envs/snowpark_env/bin/python"

B."python.pythonPath": "Ipath/to/anaconda3/envs/snowpark_env/bin/python"

C."snowflake.python.defaultlnterpreterPath": "Ipath/to/anaconda3/envs/snowpark_env/bin/python"

D."python.defaultlnterpreterPath": "Ipath/to/anaconda3/envs/snowpark_env/bin/python"

E."snowsql.pythonPath": "/path/to/anaconda3/envs/snowpark_env/bin/python"

Question 102

You are tasked with creating a Snowpark stored procedure that needs to access a secret stored in Snowflake's Secret Managen The secret contains credentials required to connect to an external API. Which of the following steps are necessary to correctly and securely access and use the secret within your Snowpark stored procedure? (Select all that apply)

A.Grant the USAGE privilege on the secret to the role that will execute the stored procedure.

B.Use the method within the stored procedure to retrieve the secret value.

C.Store the secret value directly in the stored procedure's code as a global variable.

D.Ensure that the stored procedure is created with the 'EXECUTE AS CALLER clause.

E.Create a UDF that exposes the secret and call that UDF in the stored procedure.

Question 103

You need to create a Snowpark DataFrame using a SQL query. The query requires a user-defined variable (e.g., a date for filtering records). What are the correct and recommended ways to safely pass this variable into the SQL query when creating the DataFrame using 'session.sql()' to prevent SQL injection vulnerabilities?

Question 104

You are developing a Snowpark application that processes large datasets stored in Snowflake. You need to implement custom User-Defined Functions (UDFs) written in Java. The UDF requires specific third-party libraries that are not available in the default Snowflake Java environment. What steps are necessary to package and deploy these UDFs correctly?

A.Package the Java code and dependencies into a JAR file and upload it to a Snowflake stage. Use the 'CREATE FUNCTION' command with the 'IMPORTS' clause to reference the JAR file.

B.Use the 'CREATE OR REPLACE JAVA FUNCTION' command directly in Snowsight and paste the Java code along with the dependencies' contents into the function body.

C.Utilize the Snowpark API to create a 'snowpark.functions.udf object, including the Java code and dependencies. The Snowpark runtime will handle the deployment.

D.Compile the Java code into a native library (e.g., a .so file), upload it to a Snowflake stage, and use the 'CREATE EXTERNAL FUNCTIONS command to invoke it.

E.Create a separate Python UDF that imports the Java code using Jpype and then register the Python UDF with Snowflake

Question 105

Given a Snowpark DataFrame 'df with a column named 'data' of VARIANT type, where the VARIANT contains JSON objects with nested fields. You need to extract the value of the nested field 'address.city' as a STRING and the value of as a DOUBLE, handling cases where either 'address' or 'items' might be missing. Which combination of Snowpark functions is best suited to achieve this robustly and efficiently?