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In the context of Azure Databricks, you are tasked with optimizing a real-time data processing pipeline that involves stream-static joins using Delta Lake. The pipeline must efficiently explore and tune state information to handle high-volume data streams with low latency. Considering the requirements for scalability, cost-effectiveness, and compliance with data governance policies, which of the following approaches is the BEST for exploring and updating state information in this scenario? Choose the correct option from the four provided.
A
Utilize the 'state' function directly within a stream-static join to access and manipulate state information without any additional overhead.
B
Implement the 'mapGroupsWithState' function to explore and update state information, allowing for custom state management and emission of updated results based on incoming data.
C
Apply the 'flatMapGroupsWithState' function for exploring and updating state information, which supports more complex state operations but may introduce additional processing overhead.
D
Rely on the 'updateStateByKey' function for state updates, which is simpler but less flexible and scalable for high-volume streams.