Databricks Machine Learning Associate Question 436: You are working on a machine learning project and have engineered a... | Databricks Machine Learning Associate Dumps

Databricks Machine Learning Associate practice question 436 of 656

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

Databricks Machine Learning Associate Question 436

Select 3

You are working on a machine learning project and have engineered a new set of features for your model. You want to store these features in a Databricks Feature Store table for reuse across multiple models. Which of the following steps are required to write the data to the feature store table?

A
Define a feature store client using the FeatureStoreClient class.
B
Ensure that the data being written is in the form of a Spark DataFrame.
C
Use the create_table method from the feature store client to save the features.
D
Specify a unique primary key for the feature store table.
E
Directly write the feature data to the feature store table using spark.write.table().

Show answer and explanation

Correct answers: A, B, D

Explanation

To write data to a feature store table in Databricks, you need to first initialize a FeatureStoreClient, ensure the data is in the form of a Spark DataFrame, and specify a unique primary key for the table. The FeatureStoreClient provides the appropriate methods for writing data, rather than directly using spark.write.table(). Properly understanding these requirements ensures efficient feature management and reuse.

A. Correct.
Correct. To interact with the Databricks Feature Store, you must create an instance of the FeatureStoreClient class.
B. Correct.
Correct. The Databricks Feature Store expects the data being written to be in the form of a Spark DataFrame.
C. Incorrect.
Incorrect. The create_table method is used to define a new feature store table, but it is not used directly to write feature data. Writing data typically requires the write_table method.
D. Correct.
Correct. A unique primary key is required to identify individual feature records in the feature store table.
E. Incorrect.
Incorrect. You cannot directly use spark.write.table() to write to a feature store table. The Feature Store has its own API for managing and writing data.

Databricks Machine Learning Associate practice question 436 of 656

Databricks Machine Learning Associate Question 436

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