QuestionQ36
Advanced Feature Store ConceptsA machine learning engineer developed a model and registered it by using the FeatureStoreClient fs. The model has model URI model_uri. The engineer must now run batch inference on the customer-level Spark DataFrame spark_df, but it lacks several static features that were used to train the model. The customer_id column is the primary key of spark_df and of the training set used to train and log the model.
Which code block can compute predictions for spark_df when the missing feature values can be located in the Feature Store by searching for features using customer_id?
- A df = fs.get_missing_features(spark_df, model_uri)fs.score_model(model_uri, df)
- B fs.score_model(model_uri, spark_df)
- C df = fs.get_missing_features(spark_df, model_uri)fs.score_batch(model_uri, df)
- D df = fs.get_missing_features(spark_df)fs.score_batch(model_uri, df)
- E fs.score_batch(model_uri, spark_df)
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