SPS-C01 Exam Dumps | Consider a DataFrame 'products df loaded from a SnoMlake table. It contains a 'features' column of type

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Snowflake.SPS-C01.v2026-08-07.q151
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Question 14/151

Consider a DataFrame 'products df loaded from a SnoMlake table. It contains a 'features' column of type VARIANT, where each row contains a JSON object representing product features. Your task is to create a new DataFrame where each feature becomes a separate column. You need to dynamically extract these features without knowing the specific feature names in advance. Which of the following approaches could achieve this using Snowpark, and what considerations are important? Choose all that apply:

A. Use a User-Defined Function (UDF) to parse the JSON and return a dictionary. Then, use a loop to iterate over the keys in the dictionary and create new columns based on these keys.

B. Use the function on the VARIANT column to get an array of feature names. Then, use a loop to iterate over this array and dynamically create new columns using bracket notation (e.g.,

C. Use the 'FLATTEN' function within a Snowpark DataFrame transformation. This allows you to transform the key-value pairs within the VARIANT column into separate rows, which can then be pivoted to create new columns.

D. It's not possible to dynamically extract feature names and create columns in Snowpark without knowing the schema in advance.

E. The function can be used in conjunction with a Snowpark SQL query to dynamically extract the json into separate columns.

Correct Answer: B,C

Options B and C are viable approaches. Option B: You can use the native function on the VARIANT column to extract the keys, then iterate over the returned array to dynamically create new columns. This relies on knowing the structure of the data at runtime, but doesn't require a UDE Option C: FLATTEN' offers a SQL-centric way to achieve this, which might be preferable for performance and maintainability. After flattening, you would typically pivot the data. Option A is possible with IJDFs, but might be less performant than using native functions or FLATTEN. Option D is incorrect; dynamic column creation is possible. While OBJECT_CONSTRUCT() can construct JSON objects, it's not directly helpful for dynamically extracting JSON properties into separate columns in this scenario (Option E).

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