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Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You're developing a Snowpark Python application to process log files stored in an external stage 's3_logs'. These logs are in plain text, with each line representing a log entry. You need to filter log entries based on a specific keyword and extract timestamps from the matching lines. Which of the following approaches, using and Snowpark DataFrames, will efficiently accomplish this, avoiding unnecessary data transfer to the client?

A) Use 'session.read.option('PATTERN', ' to load all log files into a Snowpark DataFrame with a single column containing the log lines. Create a UDTF that reads a partition of the DataFrame, filters lines based on the keyword, extracts timestamps, and returns a table of timestamps.
B) Use pattern=' .log')' to load all log files into a Snowpark DataFrame with a single column containing the log lines. Then, filter the DataFrame using like' to find lines containing the keyword and extract timestamps using regular expressions in a subsequent select statement.
C) Download each log file using 'SnowflakeFile.get' , read the file line by line in the client application, filter lines based on the keyword, extract timestamps, and then create a Snowpark DataFrame with the extracted timestamps.
D) Create a UDF that accepts a 'SnowflakeFile' object as input, reads the file line by line inside the UDF, filters lines based on the keyword, extracts timestamps, and returns a list of timestamps. Call this UDF on a Snowpark DataFrame created using 'session.read.option('PATTERN', ' .10g').format('CSV').load('@s3_logs'V.
E) Create an external function that accesses the files directly from S3, performs the filtering and timestamp extraction, and returns the results. Then create a Snowpark DataFrame to invoke the external function.

2. A Snowpark application needs to process a large dataset (1 TB) residing in Snowflake, performing complex transformations. Due to network constraints and the complexity of the transformations, the execution takes a considerable amount of time. The application's end-users are complaining about the latency. Which of the following strategies would MOST effectively enhance performance, specifically targeting the reduction of overall execution time considering the synchronous vs. asynchronous execution models and the implications of the 'block' parameter?

A) Implement asynchronous actions with 'block=False' to initiate transformations without waiting for completion, allowing other parts of the application to proceed concurrently. Subsequently, use a mechanism (e.g., polling, callbacks) to retrieve the results when available, leveraging parallel execution to enhance overall responsiveness.
B) Utilize synchronous actions to trigger transformations and retrieve results; this approach guarantees immediate availability but might not be optimal for long-running, complex operations.
C) Employ asynchronous actions with 'block=True' to immediately retrieve results, ensuring data consistency but potentially increasing overall latency due to blocking.
D) Increase the Snowflake warehouse size to improve compute capacity, regardless of the synchronous or asynchronous execution model.
E) Minimize data transfer by applying aggressive filtering and aggregation within Snowflake before transferring data to the Snowpark application for further processing, and use synchronous action with a small warehouse size.

3. A data engineer is tasked with creating a Snowpark session using JWT authentication. They have a private key 'rsa_key.pff, a user name 'snowpark_user' , and an account identifier 'my_account'. The goal is to create a session object suitable for submitting Snowpark jobs. Which code snippet correctly demonstrates the instantiation of a session object using JWT?

A)

B)

C)

D)

E)

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

A)

B)

C)

D)

E)

5. You are developing a Snowpark application that utilizes a UDF. You need to ensure that the UDF runs with the privileges of the caller (the user executing the query). Which of the following steps are necessary to accomplish this while creating the Snowpark session?

A) The account administrator needs to explicitly grant the 'CREATE FUNCTION' privilege to the user.
B) No special steps are required when creating the Snowpark session; the UDF automatically inherits the caller's privileges.
C) After creating the Snowpark session, execute the SQL command 'ALTER SESSION SET
D) When creating the Snowpark session, explicitly set the 'privilege' parameter to 'CALLER.
E) When defining the UDF using Snowpark, ensure the argument is passed in the decorator. Create the Snowpark session as usual.

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