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.