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When dealing with complex nested JSON data representing e-commerce transactions in a Spark-based lakehouse, which method is most efficient for querying and analysis?
A
Normalize the JSON structure into multiple relational tables, creating foreign keys for nested relationships.
B
Use Delta Lake‘s schema evolution to dynamically adjust to changes in the JSON structure over time.
C
Store data in its native nested format, leveraging Spark‘s capability to query nested structures directly.
D
Flatten the JSON structure into a wide table format, duplicating parent data for each nested element.
