Databricks Data Engineer Associate exam dumps

Databricks Data Engineer Associate practice question 187 of 532

Databricks Certified Data Engineer Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Data Engineer Associate Question 187

Single answer

You are working with a dataset in Databricks that contains a column named 'orders', where each record is a JSON structure containing an array of items purchased in a single order. You want to transform this dataset so that each item in the array becomes its own row, but you also want to preserve the association with the original order ID. Which function should you use?

  1. A

    Use the explode function to transform the array into individual rows.

  2. B

    Use the flatten function to transform the array into individual rows.

  3. C

    Use the explode function, but only after converting the array into a map.

  4. D

    Use the flatten function to preserve the structure of the original dataset.

Show answer and explanation

Correct answer: A

Explanation

The explode function is specifically designed to create a new row for each element in an array, while also preserving the original structure of the dataset (e.g., the order ID in this case). The flatten function, on the other hand, is used to combine arrays of arrays into a single array and does not create new rows, making it unsuitable for this task.

  • A. Correct.

    The explode function is used to transform an array into individual rows while preserving associated data, making it the correct choice for this scenario.

  • B. Incorrect.

    The flatten function is used to merge arrays of arrays into a single array, which is not suitable for creating individual rows from array elements.

  • C. Incorrect.

    The explode function does not require converting the array into a map; it works directly on arrays, so this is incorrect.

  • D. Incorrect.

    The flatten function does not preserve the structure required to maintain individual rows for each array element along with the original order ID.

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