Databricks Certified Data Engineer - Associate

Databricks Certified Data Engineer - Associate

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In a scenario where you are working with a DataFrame 'df_employees' that includes columns 'employee_id', 'name', 'department', and 'salary', your task is to transform the 'employee_id' column, which contains arrays of integers, into a single column with all the integers using Spark SQL. Considering the need for efficiency and correctness, which of the following queries best accomplishes this task? Choose the best option.





Explanation:

Option A is the correct answer as it uses the 'flatten' function to transform the 'employee_id' column containing arrays of integers into a single column with all the integers, which is the desired outcome. Option B is incorrect because 'explode' is used to create a new row for each element in an array, which does not meet the requirement of transforming the array into a single column. Option C is incorrect for the same reason as B, plus it unnecessarily includes the original 'employee_id' column. Option D is partially correct as it uses 'flatten' but includes the original 'employee_id' column, which may not be necessary depending on the use case. Option E suggests that both A and D are correct but serve different purposes, which is true in contexts where the original 'employee_id' column is needed alongside the flattened values.