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Snowflake Certified SnowPro Specialty - Snowpark Sample Questions (Q339-Q344):
NEW QUESTION # 339
You have a Snowpark DataFrame containing sales data with columns 'sale_date', and 'sale_amount'. You need to calculate the cumulative sales amount for each product over time, ordered by 'sale_date'. Which of the following Snowpark code snippets correctly implements this using window functions?
- A.

- B.

- C.

- D.

- E.

Answer: B
Explanation:
Option A is correct. It correctly uses to group by 'product_id' and 'order_by' to sort by 'sale_date' within each product group. It then calculates the cumulative sum using Options B, C, D and E contain typos or incorrect function usage or order of arguments. 'cumulative_surn' is not a standard function provided.
NEW QUESTION # 340
You're working with Snowpark and have a DataFrame 'df containing a column 'json_data' with JSON strings. Some of these JSON strings are invalid. You need to parse the valid JSON strings and extract a field named 'product_id' from them. Invalid JSON strings should result in a 'NULL' value for the extracted 'product_id'. Which of the following approaches is the MOST robust and efficient way to achieve this?
- A.

- B.

- C.

- D.

- E.

Answer: B
Explanation:
Option B is the most robust and efficient. handles invalid JSON strings gracefully by returning 'NULL'. The other options have drawbacks: Option A will throw an error if the JSON is invalid. Option C involves a UDF, which can be slower than built-in functions. Option D assumes valid json and uses the native notation which will error with invalid JSON data. Option E uses Regex which is not recommended and can have perfomance impact as well as not robust
NEW QUESTION # 341
Which of the following statements are correct regarding the authentication methods available when creating a Snowpark session?
- A. OAuth authentication requires pre-configuration in Snowflake and typically involves client IDs, client secrets, and refresh/access tokens.
- B. Snowflake supports MFA(Multi-Factor Authentication) using Web Browser Authentication, which needs to be enabled at an account level.
- C. Using username/password authentication is the most secure and recommended approach for production environments.
- D. OAuth with external Oauth providers (like Okta or Azure AD) is not supported in snowpark, and only username password can be used.
- E. Key pair authentication uses a private key to establish a secure connection without needing to store passwords directly in the code.
Answer: A,B,E
Explanation:
Options B, C, and D are correct. OAuth provides a secure delegation mechanism. Key pair authentication is also a secure method, eliminating password storage in code. Snowflake Browser-Based MFA relies on web browser redirection. Option A is incorrect because username/password is generally less secure than key pair or OAuth. Option E is incorrect because External Oauth providers like Okta are Azure AD is supported for authentication using a federated OAuth flow.
NEW QUESTION # 342
A data engineer is tasked with creating a Snowpark Python application that needs to access data from multiple Snowflake accounts and regions. All accounts are using Snowflake's Business Critical edition. Which of the following approaches would be the MOST efficient and maintainable for managing and switching between different Snowpark sessions in this scenario?
- A. Create a new Anaconda environment for each Snowflake account and install the necessary packages in each environment.
- B. Create separate Python scripts for each account and region, hardcoding the account identifiers and credentials within each script.
- C. Create a configuration file (e.g., YAML or JSON) that stores the account identifiers and other connection details for each Snowflake account and region. Load this configuration and create separate Snowpark session objects for each account, storing them in a dictionary or list.
- D. Use a single Snowpark session object and dynamically update the connection parameters (account identifier, username, password) whenever switching to a different account and region.
- E. Use the 'snowflake.connector.connect' method to directly establish connections without using the Snowpark Session object.
Answer: C
Explanation:
Storing connection details in a configuration file and creating separate Snowpark session objects is the most maintainable and efficient approach. It allows for easy switching between accounts and regions without modifying the core application logic. Option A is not scalable. Option B is risky because changing connection parameters on a live session can lead to unexpected behavior. Option D bypasses Snowpark functionalities. Option E is an overkill.
NEW QUESTION # 343
A data science team wants to operationalize a Snowpark Python UDF that performs sentiment analysis on customer reviews. The UDF, 'analyze sentiment(review_text)', is currently defined within a Snowpark session. Which of the following approaches is the MOST efficient and scalable way to deploy this UDF for real-time scoring of incoming review data in a Snowflake table named 'CUSTOMER REVIEWS'?
- A. Call the 'analyze_sentiment' UDF directly within a Snowpark DataFrame transformation that reads from 'CUSTOMER_REVIEWS'.
- B. Create a Snowpark Dataframe that reads from 'CUSTOMER_REVIEWS , convert it to pandas dataframe and call analyze_sentiment function on pandas dataframe.
- C. Register the 'analyze_sentiment' UDF as a persistent UDF in Snowflake and then call it from a SQL query that reads from 'CUSTOMER REVIEWS.
- D. Persist the Snowpark session with UDF definition using pickle and call it from another Snowpark session.
- E. Package the 'analyze_sentiment' function as a stored procedure and execute it using Snowpark session.execute.
Answer: C
Explanation:
Registering the UDF as a persistent UDF in Snowflake allows it to be called directly from SQL, leveraging Snowflake's query engine for optimal performance and scalability. Option A keeps the transformation entirely within Snowpark, which is a valid approach, but less scalable. Option C involves converting to a Pandas DataFrame, which moves data outside of Snowflake and negates its benefits. Option D creates a stored procedure that is correct but the question ask to perform in real time so it's not ideal. Option E is not the way to persist Snowpark with UDF.
NEW QUESTION # 344
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