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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 representing sensor data. The DataFrame contains columns like 'timestamp', 'sensor id' , and 'value'. You need to perform a complex windowing operation to calculate the moving average of the 'value' for each 'sensor id' over a 5-minute window, but only for data points where the 'value' is greater than a threshold. The window should be defined based on the 'timestamp' column. What is the most efficient and correct approach to implement this using Snowpark DataFrames?

A) Create a UDF that takes a list of timestamps and values as input and returns the moving average. Apply this UDF to the entire DataFrame.
B) First, collect the entire DataFrame into a Pandas DataFrame, then use Pandas windowing functions to calculate the moving average.
C) Use a loop to iterate over each 'sensor_id' , filter the DataFrame for that sensor, calculate the moving average using Pandas windowing functions, and then combine the results.
D) First apply the moving average calculation to the DataFrame and then filter for rows with values exceeding the threshold, since calculations are performed in order.
E) Use a combination of 'filter' to apply the threshold condition, 'Window.partitionBy' and 'Window.orderBy' to define the window, and 'avg' window function to calculate the moving average.

2. You are developing a Snowpark Python stored procedure that utilizes external Python libraries (e.g., 'requests', 'numpy'). What are the recommended steps for deploying this stored procedure to Snowflake, ensuring that all necessary dependencies are available during execution?

A) Include the installation commands (e.g., 'pip install requestS , 'pip install numpy') directly within the stored procedure's Python code. Snowflake will execute these commands during each invocation of the stored procedure.
B) List all required dependencies in the 'packages' parameter when creating the stored procedure. Snowflake automatically resolves and installs these dependencies from its managed Anaconda channel.
C) None of the above, Snowflake does not support external python libraries in stored procedures.
D) Both A and B are correct methods to deploy the stored procedure.
E) Package all required dependencies into a ZIP file and upload it to a Snowflake stage. Specify the stage path in the 'imports' parameter when creating the stored procedure.

3. You have a Snowpark DataFrame with columns 'department' , and 'salary'. You want to identify employees in each department whose salary is within the top 20% of salaries for that department. Which of the following approaches, using window functions, is the MOST efficient way to achieve this?

A) Use the 'ntile(5)' window function to divide each department's employees into 5 buckets based on salary, then select employees in the top bucket.
B) Use the window function to calculate the percentile rank of each employee's salary within their department, then filter for ranks greater than or equal to 0.8.
C) Calculate the maximum salary per department, then filter employees whose salary is greater than or equal to 80% of the maximum salary.
D) Calculate the average salary per department, then filter employees whose salary is greater than 80% of the average salary.
E) Use window function to rank employees within each department by salary, then calculate the 80th percentile salary using a separate aggregation and join back to the original DataFrame to filter.

4. You have a complex data pipeline implemented using Snowpark Tasks in a Directed Acyclic Graph (DAG). One of the tasks, , depends on the successful completion of two parent tasks, and 'task B'. You need to implement error handling such that if 'task_R fails, 'task_C' should not be executed, but should still complete its execution regardless of status. If 'task B' fails, 'task_C' should not be executed. How do you configure the task dependencies and error handling in Snowflake to achieve this behavior?

A)

B)

C)

D)

E)

5. Consider the following Python code snippet using Snowpark:

Which of the following statements are true regarding this Snowpark code?

A) The code calculates the sum of the 'sales' column, grouped by 'category' , and saves the result to a new table named , overwriting it if it exists.
B) The code will fail because password authentication is deprecated and replaced by Key Pair authentication.
C) The code uses best practices by explicitly closing the Snowflake session, preventing resource leaks.
D) The code reads data from a table named 'my_table' in Snowflake.
E) The code establishes a connection to Snowflake using the provided credentials.

Solutions: