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Snowflake SPS-C01 Exam Syllabus Topics:

Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You are developing a Snowpark Python application to process large datasets stored in a Snowflake table called 'CUSTOMER DATA' The application needs to perform complex data transformations and aggregations that benefit from Snowpark's lazy evaluation and query optimization. Which of the following approaches will lead to the MOST efficient execution in terms of resource utilization and performance?

A) Fetch all the data from 'CUSTOMER_DATR into a Pandas DataFrame using , perform the transformations in Pandas, and then load the results back into a new Snowflake table using 'session.write_pandas()'.
B) Load the data into a temporary table, then create a Stored Procedure in SQL to perform transformations, and call the procedure from the Snowpark Python application.
C) Use 'session.table('CUSTOMER to fetch all the data into a list of Row objects in Python, perform transformations using standard Python loops and data structures, and then write the processed data to a new Snowflake table using 'session.createDataFrame(V.
D) Execute a series of individual SQL queries using 'session.sql()' to perform the transformations and aggregations, and then combine the results into a final Pandas DataFrame for further processing before loading it back into Snowflake.
E) Create a Snowpark DataFrame from the "CUSTOMER_DATX table using 'session.table('CUSTOMER DATA')', perform all the transformations and aggregations using Snowpark DataFrame API, and materialize the final result into a new Snowflake table using .

2. You are tasked with automating the creation of Snowpark sessions using key pair authentication for multiple users. You have a function that retrieves connection parameters (account, user, private key, etc.) for each user from a secure configuration file. The private keys are stored in PEM format. However, some users' private keys are password-protected. Which of the following approaches ensures the secure and correct establishment of Snowpark sessions for all users, including those with password-protected private keys? Assume get_user config(username)' retrieves the user's configuration, including the private key and password (if any).

A)

B)

C) Attempt to establish a session without a password. If it fails, prompt the user for the password and retry the session creation using the provided password. Store the password temporarily in memory.
D) Store the password for each user's private key in a separate, encrypted file and retrieve it during session creation.
E) Require all users to remove the password protection from their private keys to simplify the session creation process.

3. You are developing a Snowpark stored procedure to process PDF files stored in a Snowflake stage. You need to extract text from these PDF files and store the extracted text in a Snowflake table. Due to security requirements, you cannot use any external packages that require internet access. Which of the following approaches can you use to accomplish this task securely and efficiently? (Select all that apply)

A) Implement an external function using AWS Lambda or Azure Functions to parse the PDF files and extract the text. Configure the external function to have no internet access.
B) Use Snowpark's built-in PDF parsing functions to extract the text. Snowflake provides native support for PDF parsing, eliminating the need for external libraries.
C) Develop a custom Java UDF (User-Defined Function) that uses a secure, open-source PDF parsing library (e.g., PDFBox) and register it with Snowflake. Call this UDF from the Snowpark stored procedure to extract the text.
D) Use the function to read the PDF files as binary data. Implement a pure-Python PDF parsing library directly within the stored procedure to extract the text. Ensure the library code is included directly in the stored procedure code.
E) Convert the PDF files to a text-based format (e.g., TXT) using an external tool before loading them into Snowflake. Then, use Snowpark to process the text files.

4. You have a Snowpark DataFrame 'sales df with columns 'product_id' (INTEGER), 'sale date' (DATE), and 'sale_amount' (DOUBLE). You need to filter the DataFrame to include only sales that occurred in the year 2023 and where the 'sale_amount' is greater than the average 'sale_amount' for that specific 'product id'. Which of the following Snowpark Python code snippets will correctly achieve this?

A)

B)

C)

D)

E)

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

Solutions: