What code would correctly define a function to return new, unprocessed records from a Delta table?

The chosen code correctly utilizes the spark.readStream.table("bronze") method to define a function that returns new, unprocessed records from a Delta table named "bronze." In a streaming context, spark.readStream is employed specifically to read data in real-time as it is added to the source table. By using the table method, it specifies that the reading should occur on a Delta table that has been registered in the metastore.

Delta Lake is designed to handle streaming data efficiently, allowing you to manage both batch and streaming scenarios seamlessly. When querying a table that supports streaming, using spark.readStream ensures that the application can consume data continuously, capturing any newly added records after the last read operation.

Other options do not provide the correct behavior for streaming data:

• Reading from a local table as in the first option does not support the streaming capability, as it is primarily intended for batch retrieval of data.

• The method spark.readStream.load("bronze") is used for loading data from files in a directory format rather than from a registered Delta table.

• The last choice, return spark.read.table("bronze"), indicates a batch read of data from the Delta table, failing to