SPS-C01 Exam Dumps | A data engineering team is developing a Snowpark application to process large volumes of data'. They

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Question 52/151

A data engineering team is developing a Snowpark application to process large volumes of data'. They aim to leverage session parameters for fine-grained control over query execution and resource allocation. Which of the following methods is the MOST efficient and secure way to set session parameters, ensuring that sensitive information like warehouse size and query timeouts are dynamically adjusted based on the workload without hardcoding values in the application?

A. Directly using 'session.sql('ALTER SESSION SET QUERY _ TIMEOUT = for each session.

B. Using environment variables to store parameter values and accessing them via 'os.environ['WAREHOUSE SIZET within the Snowpark application.

C. Using the 'snowsqr CLI tool to pre-configure session parameters before running the Snowpark application.

D. Leveraging Snowflake's parameter hierarchy by setting account-level parameters and inheriting them into the Snowpark session.

E. Utilizing Snowpark session builder to set parameters using a dictionary read from a secure configuration file, then overriding defaults based on workload characteristics. Example: 'session = Session.builder.configs(config).config('warehouse', workload_optimized_warehouse).create()'

Correct Answer: E

Option E is the most efficient and secure because it allows for a combination of pre-configured parameters from a secure source (like a configuration file) and dynamic overrides based on the specific workload. This ensures that the application can adapt to different processing needs without exposing sensitive information or hardcoding values. Account level parameters are too broad (D), Direct SQL execution is inefficient (A), Environment Variables are less secure (B), and CLI is not dynamic for in-application session settings (C).

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