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Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You are tasked with creating a Snowpark UDTF (User-Defined Table Function) in Python to process a large CSV file stored in a Snowflake stage. Each row in the CSV represents a transaction, and you need to parse each row and extract specific fields based on a complex set of rules. The UDTF should return a table with the extracted fields. Consider the following code snippet:

A) The UDTF will execute correctly and efficiently in Snowpark, correctly processing each row of the CSV and returning the extracted fields as a table.
B) The code will raise an error because the 'read_csvs function is not available within the Snowpark UDTF context. The input needs to be processed differently.
C) The UDTF will fail because the 'yield' statement is being called after using 'return' in the processing block. Remove the yield statement as it is incompatible.
D) The UDTF will run but will not return any data since the code currently lacks a 'session' object properly initialized for Snowpark operations inside the handler. Ensure the handler method has the session parameter and uses it.
E) The UDTF will run, but it will be slow due to the use of pandas DataFrame operations within the UDTF. Consider optimizing the code to use Snowpark DataFrame operations instead.

2. A Snowpark developer is using to create a Snowpark session. They want to ensure that the session uses a specific role and warehouse, but only if those parameters are not already defined in the Snowflake CLI configuration. Which of the following code snippets correctly implements this behavior?

A)

B)

C)

D)

E)

3. You have a Snowpark DataFrame 'df_orders' containing order data'. You want to delete all records from the underlying Snowflake table 'ORDERS TABLE' where the 'order_date' is older than '2023-01-01' using a Snowpark DataFrame operation. Which of the following code snippets is the MOST efficient and recommended way to achieve this, assuming 'spark' is your Snowpark Session object?

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

4. You have JSON files stored in an internal stage named 'json_stage' within your Snowflake account. Each JSON file contains an array of product objects, with potentially nested structures. You need to create a Snowpark DataFrame to analyze this data, but the schema is complex and you want to avoid explicitly defining it in your Python code. Which of the following Snowpark code snippets will MOST effectively achieve this, assuming you have a Snowpark session object named 'session'?

A)

B)

C)

D)

E)

5. You are developing a Snowpark application in Python to perform sentiment analysis on customer reviews stored in a Snowflake table named 'CUSTOMER_REVIEWS. The table has columns 'REVIEW ONT), 'REVIEW TEXT (VARCHAR), and 'SENTIMENT SCORE (FLOAT). You want to define a UDF using Snowpark that leverages a pre-trained sentiment analysis model from the 'nltk' library (already uploaded to a stage). The UDF should take 'REVIEW TEXT' as input and return the sentiment score. Which of the following code snippets will correctly define and register the UDF, ensuring it's accessible for use in Snowpark DataFrames, taking into account potential serialization issues with 'nltk' models?

A)

B)

C)

D)

E)

Solutions: