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Snowflake SPS-C01 Exam Syllabus Topics:

Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

Question 1

A data engineer is tasked with calculating a 3-month rolling average of sales data using Snowpark Python. The sales data is stored in a table named 'SALES DATA' with columns 'sale_date' (DATE) and (NUMBER). They need to use a table function to accomplish this efficiently. Which of the following Snowpark Python code snippets correctly implements this rolling average calculation using a table function?

A.

B.

C.

D.

E.

Question 2

You have a Snowpark DataFrame named with columns 'category', , and You want to perform the following transformations using Snowpark:

A.

B.

C.

D.

E.

Question 3

You need to perform a set difference operation between two DataFrames in Snowpark Python. 'dfl' contains customer IDs from a marketing campaign, and 'df2 contains customer IDs from a recent purchase event. You want to identify customers who were targeted in the campaign but did not make a recent purchase. Both DataFrames have a column named 'customer id'. Which of the following approaches provides the most efficient way to accomplish this task in Snowpark?

A.

B.

C.

D.

E.

Question 4

Consider the following Snowpark Python code snippet designed to create a DataFrame and then register a custom function (UDF):

This code runs successfully. However, you need to deploy this as a stored procedure. What minimal changes are required to make this code runnable as a Snowpark Python stored procedure and callable from SQL?

A. The 'return df.collect()' line must be replaced with 'return and 'return_type' and 'input_typeS arguments of udf must be removed. The rest of the code remains unchanged.
B. No changes are required; the code will function as a stored procedure as is.
C. The 'return df.collect()' line must be replaced with 'return and the 'return_type' and 'input_typeS arguments of udf must be removed to allow inference. The rest of the code remains unchanged.
D. The 'return df.collect()' line must be replaced with 'return and the Snowflake session object must be explicitly passed to the UDF when it is called.
E. The 'return df.collect()' line must be replaced with 'return df and create a DataFrame. The rest of the code remains unchanged.

Question 5

Consider a Snowpark DataFrame with columns 'DEPARTMENT, 'SALARY , and 'YEAR. You want to find the average salary for each department over all years and then filter the departments to only include those where the average salary is greater than 100000. Which of the following approaches is the MOST efficient and correct way to achieve this using Snowpark Python?

A.

B.

C.

D.

E.

Solutions: