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Exam Certified Machine Learning Professional All Questions

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Exam Certified Machine Learning Professional topic 1 question 15 discussion

Actual exam question from Databricks's Certified Machine Learning Professional
Question #: 15
Topic #: 1
[All Certified Machine Learning Professional Questions]

A data scientist has computed updated feature values for all primary key values stored in the Feature Store table features. In addition, feature values for some new primary key values have also been computed. The updated feature values are stored in the DataFrame features_df. They want to replace all data in features with the newly computed data.
Which of the following code blocks can they use to perform this task using the Feature Store Client fs?

  • A.
  • B.
  • C.
  • D.
  • E.
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Suggested Answer: D 🗳️
by BokNinja at Dec. 19, 2023, 5:14 a.m.

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hugodscarvalho
9 months, 1 week ago
Selected Answer: D
The data scientist already has the table created, so the method should be "write_table". Since he wants to replace all data in features with the newly computed data the "mode" overwrite should be used. Doc: https://docs.databricks.com/en/machine-learning/feature-store/workspace-feature-store/feature-tables.html#create-a-feature-table-in-databricks-feature-store
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mozuca
10 months, 1 week ago
Selected Answer: D
Alternatively, you can create_table with schema only (without df), and populate data to the feature table with fs.write_table, fs.write_table has both overwrite and merge mode. Example: fs.create_table( name=table_name, primary_keys=["index"], schema=airbnb_df.schema, description="Original Airbnb data" ) fs.write_table( name=table_name, df=airbnb_df, mode="overwrite" ) Is this case the answer is D
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BokNinja
10 months, 2 weeks ago
Answer is D. The mode='overwrite' argument ensures that the existing data in the feature table is replaced with the new data from features_df1.
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