Databricks Generative AI Engineer Associate Question 95
Select 3You are tasked with creating a tool to extract data from a semi-structured JSON file stored in a Databricks workspace. The data will be used to train a generative AI model. Which of the following steps are necessary to correctly extract and prepare the data for further processing?
- A
Use the Databricks
spark.read.json()function to load the JSON file into a DataFrame. - B
Directly pass the JSON file path to the generative AI model without further processing.
- C
Use Spark SQL or DataFrame operations to flatten nested structures in the JSON data if required.
- D
Cache the DataFrame immediately after loading the JSON file to optimize performance for subsequent operations.
- E
Ensure that the schema of the loaded JSON data is inferred or explicitly provided before performing transformations.
Show answer and explanation
Correct answers: A, C, E
Explanation
To extract data from a semi-structured JSON file for generative AI tasks, you need to load the data into a DataFrame using spark.read.json(), ensure the schema is correctly handled, and flatten any nested structures as necessary. These steps prepare the data for further processing and analysis. Caching is optional and depends on the use case, while raw JSON data cannot be directly passed to a model without preparation.
- A. Correct.
Correct: The
spark.read.json()function is specifically used to load JSON files into a Spark DataFrame in Databricks, making it a necessary step for extracting JSON data. - B. Incorrect.
Incorrect: Passing the raw JSON file directly to the generative AI model is not feasible because the data needs to be extracted, cleaned, and transformed into a suitable format first.
- C. Correct.
Correct: Flattening nested structures in a JSON file is often required to make the data easier to process and analyze, especially for training machine learning models.
- D. Incorrect.
Incorrect: While caching can improve performance in iterative operations, it is not a mandatory step for data extraction and preparation. It depends on the specific workflow and usage patterns.
- E. Correct.
Correct: Ensuring the schema is inferred or explicitly defined is critical for handling semi-structured data correctly and avoiding unexpected errors during transformations.