SPS-C01 Exam Dumps | You have a Snowflake table named 'CUSTOMER DATA' with columns 'CUSTOMER ID', 'NAME, 'CITY , and 'ORDER

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Snowflake.SPS-C01.v2026-08-07.q151
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Question 123/151

You have a Snowflake table named 'CUSTOMER DATA' with columns 'CUSTOMER ID', 'NAME, 'CITY , and 'ORDER COUNT. You want to create a Snowpark DataFrame named 'customer_df containing only customers from 'New York' with an 'ORDER COUNT greater than 10. Which of the following code snippets is the MOST efficient and correct way to achieve this, minimizing data transfer and maximizing pushdown optimization to Snowflake?

Correct Answer: A

Option A is the most efficient. It directly uses the 'filter' method with the combined condition, allowing Snowpark to push down the entire filter to Snowflake for execution. Option B uses 'session.sqr, which might not be as optimized as using the table API directly. Option C pulls the entire table into Pandas, which is highly inefficient for large tables, defeating the purpose of Snowpark. Option D, while functional, is less readable than A, and the multiple 'where' calls are logically equivalent to a single 'filter' with combined conditions. Option E, while functional, contains redundant 'select(' 'V operation.

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