Snowflake Certified SnowPro Specialty - Snowpark: SPS-C01 Exam


"Snowflake Certified SnowPro Specialty - Snowpark", also known as SPS-C01 exam, is a Snowflake Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 374 Q&As to your SPS-C01 Exam preparation. In the SPS-C01 exam resources, you will cover every field and category in Snowflake Certification Certification helping to ready you for your successful Snowflake Certification.

  • Exam Code: SPS-C01
  • Exam Name: Snowflake Certified SnowPro Specialty - Snowpark
  • Total Questions: 374

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Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. A data scientist has developed a complex machine learning model in Python that needs to be operationalized within a Snowpark pipeline. This model depends on several custom Python packages not available in Snowflake's default environment. The data scientist wants to define a UDTF to apply this model to incoming data'. Which of the following steps are NECESSARY to successfully deploy and execute this UDTF in Snowflake? (Select three)

A) Specify the stage location in the 'imports' clause of the 'CREATE FUNCTION' statement when defining the UDTF.
B) Upload the ZIP file to a Snowflake stage.
C) Create a virtual environment and install all the required Python packages.
D) Include only custom packages into the ZIP file and exclude common python library packages, as snowpark is pre-installed.
E) Package the virtual environment as a ZIP file.


2. You are tasked with building a Snowpark application that processes sensor data. The data arrives continuously and is ingested into a Snowflake table called 'RAW SENSOR DATA'. You need to create a Snowpark DataFrame that applies a user-defined function (UDF) to each row to enrich the data. The UDF, named 'ENRICH SENSOR DATA, is written in Python and resides in a stage called 'UDF STAGE. The UDF takes three arguments: 'timestamp', and 'raw_value', all of which are STRING type in Snowflake. Which of the following code snippets correctly defines and calls the UDF using Snowpark?

A)

B)

C)

D)

E)


3. You have a Python function named 'process data' that performs data cleaning and transformation on a Pandas DataFrame. You want to convert this function into a Snowpark Python stored procedure to leverage Snowflake's compute resources. However, the 'process_data' function relies on several external Python libraries (e.g., 'pandas', 'numpy', 'scikit-learn') that are not pre-installed in the Snowflake environment. Which of the following approaches would ensure that these dependencies are available within the Snowpark stored procedure? Choose all that apply

A) Use session.custom_package to resolve dependencied
B) Include the necessary 'import' statements for the libraries within the stored procedure's code. Snowflake will automatically resolve and install the dependencies.
C) Bundle the required libraries into a ZIP file and upload it to a Snowflake stage. Then, add the ZIP file to the 'imports' list during stored procedure creation, ensuring that the library paths are correctly referenced within the Python code.
D) Specify the required packages in the 'packages' argument of the '@sproc' decorator or 'session.add_packageS method.
E) Create a custom Anaconda environment with the required packages and upload it to a Snowflake stage. Then, specify the stage location in the 'imports' argument of the 'CREATE PROCEDURE statement.


4. 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?

A)

B)

C)

D)

E)


5. A Snowpark application connects to Snowflake using key pair authentication. After several successful executions, the application starts failing with authentication errors. You suspect an issue with the private key. Considering best practices for security and troubleshooting, which of the following actions should you take FIRST to diagnose and resolve the problem?

A) Check the Snowflake login history in ACCOUNT _ USAGE view to identify the specific error message and the IP address from which the failed login attempts originated. Use new authtype and password.
B) Restart the Snowpark application server to refresh the session and clear any cached credentials.
C) Rotate the public/private key pair immediately and update the Snowpark application with the new private key. Generate new username and password.
D) Immediately revoke the user's access to Snowflake and create a new user with a different private key.
E) Verify that the private key file exists at the specified path in the Snowpark application configuration and that the user running the application has read permissions on the file.


Solutions:

Question # 1
Answer: A,B,C
Question # 2
Answer: D
Question # 3
Answer: C,D
Question # 4
Answer: C,E
Question # 5
Answer: E

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