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Exam Certified Generative AI Engineer Associate All Questions

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Exam Certified Generative AI Engineer Associate topic 1 question 34 discussion

Actual exam question from Databricks's Certified Generative AI Engineer Associate
Question #: 34
Topic #: 1
[All Certified Generative AI Engineer Associate Questions]

A Generative Al Engineer has successfully ingested unstructured documents and chunked them by document sections. They would like to store the chunks in a Vector Search index. The current format of the dataframe has two columns: (i) original document file name (ii) an array of text chunks for each document.
What is the most performant way to store this dataframe?

  • A. Split the data into train and test set, create a unique identifier for each document, then save to a Delta table
  • B. Flatten the dataframe to one chunk per row, create a unique identifier for each row, and save to a Delta table
  • C. First create a unique identifier for each document, then save to a Delta table
  • D. Store each chunk as an independent JSON file in Unity Catalog Volume. For each JSON file, the key is the document section name and the value is the array of text chunks for that section
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Suggested Answer: B 🗳️
by trendy01 at Oct. 26, 2024, 6:11 a.m.

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trendy01
4 weeks, 1 day ago
Selected Answer: B
B appears to be the most appropriate choice. By flattening your dataframe into one row per chunk and creating a unique identifier for each row, you can maximize search performance and maintain a manageable structure for your data.
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