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Answer: Implement a versioned Delta Lake approach, capturing each schema evolution as a new version and using views to abstract schema complexities from users.
The versioned Delta Lake approach is optimal for managing schema evolution in nested data structures while ensuring backward compatibility. Delta Lake's ACID transaction support allows for each schema change to be captured as a new version, maintaining compatibility with existing queries. Views abstract the evolving schema's complexity, offering users a consistent interface. This method efficiently handles schema changes, minimizes disruptions, and provides a clear audit trail of schema evolution.
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When dealing with evolving nested data structures in JSON format within your lakehouse, which strategy ensures efficient schema evolution management while keeping backward compatibility for downstream users?
A
Store JSON data in its native format, leveraging schema-on-read capabilities and dynamic schema inference to handle evolution.
B
Flatten JSON data into relational tables, managing schema changes through ETL versioning and backward-compatible views.
C
Utilize a schema registry that tracks versions of nested structures, applying transformations at query time to adapt to the expected schema.
D
Implement a versioned Delta Lake approach, capturing each schema evolution as a new version and using views to abstract schema complexities from users.