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Snowflake SPS-C01 Exam Syllabus Topics:

Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You are working with a Snowpark DataFrame containing employee data, including columns 'employee_id', 'first_name', 'last_name', 'salary', and 'department'. You need to perform the following transformations: 1. Concatenate 'first_name' and into a new column called separating them with a space. 2. Increase each employee's salary by a percentage based on their 'department'. Department 'Sales' gets a 10% raise, 'Marketing' gets a 15% raise, and all other departments get a 5% raise. 3. Create a new column reflecting this raise. Which of the following Snowpark code snippets achieves these transformations correctly and efficiently? (Select all that apply)

A)

B)

C)

D)

E)

2. You have a Snowpark DataFrame named 'products_df' with columns 'product_id' (INT), 'product_name' (VARCHAR), and 'price' (FLOAT). You want to create a new DataFrame called 'discounted_products df that includes all columns from 'products_df' plus a new column named 'discounted_price', which is calculated as the original price minus a discount percentage specified by the variable 'discount_rate' (e.g., 0.1 for 10%). The 'discount_rate' is stored in the database table named 'discount_table'. You want to load the rate to variable. Choose the correct ways to achieve this. (Select all that apply)

A)

B)

C)

D)

E)

3. Consider a scenario where you have a table 'EMPLOYEES' with columns 'employee id', 'department', and 'salary'. You want to delete employees who belong to either the 'HR' or 'Finance' department and have a salary less than 60000. Which of the following Snowpark DataFrame operations correctly implements this deletion?

A) Option E
B) Option C
C) Option A
D) Option D
E) Option B

4. You are developing a Snowpark application to process customer sentiment from text reviews. You have a Python function, , that utilizes a pre-trained NLP model loaded from a file on a Snowflake stage named This function returns a sentiment score (float) between -1 and 1. You need to register this function as a UDF so that it can be used within Snowpark DataFrames. Which of the following code snippets correctly registers the UDF, ensuring the NLP model is available to the function during execution?

A)

B)

C)

D)

E)

5. Consider the following Snowflake SQL statement intended to modify the properties of a Snowpark-optimized virtual warehouse named
'SNOWPARK_WH':

Which of the following statements accurately describe the expected outcome of executing this SQL statement?

A) The SQL statement will fail because you cannot modify 'WAREHOUSE_SIZE and 'MAX CLUSTER COUNT in a single SALTER WAREHOUSE statement.
B) The SQL statement will fail because the 'SCALING POLICY parameter cannot be set for Snowpark-optimized warehouses.
C) The SQL statement will execute successfully, resizing the 'SNOWPARK WI-i' warehouse to 'LARGE', setting the maximum number of clusters to 3, the minimum to 1, and enabling the 'ECONOMY' scaling policy.
D) The SQL statement will execute successfully only if the user executing it has the 'MODIFY privilege on the 'SNOWPARK_WH' warehouse.
E) The SQL statement will execute successfully after checking if 'SNOWPARK_WH' is of Snowpark-optimized warehouse type, resizing the 'SNOWPARK_WH' warehouse to 'LARGE', setting the maximum number of clusters to 3, the minimum to 1, and enabling the 'ECONOMY' scaling policy.

Solutions: