The Feature Store Client fs provides a method called create_table that can be used to create and populate a Feature Store table from a Spark DataFrame. The create_table method takes the following parameters:

name: The name of the feature table to create. It must include the database name, such as ‘recommender_system.new_table’.

primary_keys: The name or list of names of the columns that uniquely identify each row in the feature table. For example, ‘customer_id’ or [‘customer_id’, ‘date’].

df: The Spark DataFrame that contains the data to populate the feature table. It must have the same schema as the feature table, and include the primary key columns.

description: An optional string that describes the feature table.

partition_columns: An optional list of column names to partition the feature table by. For example, [‘date’, ‘region’].

online_store: An optional boolean flag that indicates whether to publish the feature table to an online store. The default value is False.

online_store_options: An optional dictionary that specifies the configuration options for the online store, such as table name, database name, and write mode. For example, {‘table_name’: ‘new_table_online’, ‘database_name’: ‘recommender_system’, ‘write_mode’: ‘overwrite’}.

The create_table method creates a Delta table with the specified name, primary keys, partition columns, and description, and writes the data from the DataFrame to the table. If online_store is True, it also publishes the feature table to an online store with the specified options. The create_table method returns a FeatureTable object that represents the feature table12

The other code blocks are incorrect because:

B. The create_table method requires the df parameter to populate the feature table with data.

C. The write method of the DataFrame does not have a mode called ‘fs’ or a path parameter. To write a DataFrame to a Delta table, the mode should be one of ‘append’, ‘overwrite’, ‘ignore’, or ‘error’, and the format should be ‘delta’. To write a DataFrame to a Feature Store table, the create_table or write_table method of the Feature Store Client should be used.

D. The create_table method does not have a function parameter. To use a Python function to compute the features, the function should be called first and the output DataFrame should be passed to the df parameter.

E. The write method of the DataFrame does not have a mode called ‘feature’ or a path parameter. To write a DataFrame to a Feature Store table, the create_table or write_table method of the Feature Store Client should be used.

References:

Feature Store Python API reference - Databricks

Work with features in Workspace Feature Store - Databricks