Databricks Data Engineer Associate Question 185
Single answerYou are working with a DataFrame in Databricks that contains a column named nested_array, which holds deeply nested arrays. Your goal is to transform the data such that each array element becomes a separate row in the resulting DataFrame. Additionally, you need to preserve the structure of other columns in the DataFrame. Which function should you use in this scenario?
- A
Use the explode function to achieve the desired transformation.
- B
Use the flatten function to achieve the desired transformation.
- C
Use the collect_list function to achieve the desired transformation.
- D
Use the pivot function to achieve the desired transformation.
Show answer and explanation
Correct answer: A
Explanation
The explode function is designed to create a new row for each element in an array or map column while preserving the structure of other columns in the DataFrame. This makes it the ideal choice for transforming nested arrays into rows in the given scenario. The flatten function, on the other hand, is used to reduce nested arrays into a single array, which does not meet the requirements of this task.
- A. Correct.
The explode function is used to transform array elements into separate rows while preserving the structure of other columns in the DataFrame. This is the correct approach for the described scenario.
- B. Incorrect.
The flatten function is used to merge nested arrays into a single array, but it does not separate array elements into rows. This is not the correct approach for this scenario.
- C. Incorrect.
The collect_list function is used to aggregate data into an array, which is the opposite of what is needed in this scenario. It does not transform arrays into rows.
- D. Incorrect.
The pivot function is used to rotate rows into columns, which is unrelated to transforming arrays into individual rows. This is not the correct approach.