Databricks Exam Databricks-Machine-Learning-Professional Topic 12 Question 29 Discussion

Actual exam question for Databricks's Databricks Certified Machine Learning Professional exam

Question #: 29
Topic #: 12

[All Databricks Certified Machine Learning Professional Questions]

A data scientist has created a Python function compute_features that returns a Spark DataFrame with the following schema:

The resulting DataFrame is assigned to the features_df variable. The data scientist wants to create a Feature Store table using features_df.

Which of the following code blocks can they use to create and populate the Feature Store table using the Feature Store Client fs?

features_df.write.mode("fs").path("new_table")

AOption A

BOption B

COption C

DOption D

Efeatures_df.write.mode('feature').path('new_table')

Show Suggested Answer

Suggested Answer: D

by Miriam at Sep 18, 2024, 01:28 AM

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Annette

3 days ago

Hmm, I'd go with Option D. The `fs.create_feature_table()` method looks like it's specifically designed for this use case.

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Alease

8 days ago

Hmm, that makes sense. Let's see what others think before making a final decision.

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Catrice

10 days ago

I disagree, I believe Option B is the right choice because it uses the Feature Store Client fs.

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Nydia

16 days ago

Option B seems the most straightforward way to create the Feature Store table. No need to overcomplicate things.

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Carey

2 days ago

User 1: I think Option B is the best choice.

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Alease

25 days ago

I think Option A is the correct code block to create the Feature Store table.

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