Answer-first summary for fast verification
Answer: Snowpark does not require that a separate cluster be running outside of Snowflake., Snowpark executes as much work as possible in the source databases for all operations including User-Defined Functions (UDFs).
Based on the community discussion and official Snowflake documentation, options C and E are the correct answers. Option C is correct because Snowpark eliminates the need for separate external clusters by performing all computations within Snowflake's infrastructure, leveraging virtual warehouses for scale and compute management. Option E is correct because Snowpark employs pushdown optimization, executing as much work as possible in Snowflake's source databases, including for operations like User-Defined Functions (UDFs), which enhances performance by minimizing data movement. The community consensus strongly supports CE (58% of votes), with multiple references to Snowflake documentation confirming these benefits. Option A is incorrect as Snowpark does not use a Spark engine; it generates optimized SQL for Snowflake's engine. Option B is incorrect because Snowpark does not set up Spark within warehouses; it uses Snowflake's native processing. Option D is misleading as Snowpark requires code adaptation for Snowflake's APIs and does not directly run unmodified Spark code.
Author: LeetQuiz Editorial Team
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What are the benefits of using Snowpark with Snowflake? (Choose two.)
A
Snowpark uses a Spark engine to generate optimized SQL query plans.
B
Snowpark automatically sets up Spark within Snowflake virtual warehouses.
C
Snowpark does not require that a separate cluster be running outside of Snowflake.
D
Snowpark allows users to run existing Spark code on virtual warehouses without the need to reconfigure the code.
E
Snowpark executes as much work as possible in the source databases for all operations including User-Defined Functions (UDFs).
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