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Answer: Leverage Delta Lake‘s time travel feature, partitioning data by change date to optimize retrieval of specific versions.
Delta Lake‘s time travel feature provides built-in support for querying previous versions of data using timestamps or version numbers, simplifying access to historical data. Partitioning data by change date optimizes query performance by enabling the system to quickly locate and retrieve the relevant partitions. This approach ensures efficient and optimized access to historical versions for compliance and auditing, without the need for complex custom solutions or additional versioning layers. It also enhances scalability and maintainability by reducing the complexity of managing historical data versions in a lakehouse environment.
Author: LeetQuiz Editorial Team
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When designing a data model in a lakehouse environment that requires frequent access to historical versions for compliance and auditing purposes, which strategy best optimizes access to these historical data points?
A
Store each version as a separate record in a flat table, using a timestamp and version identifier as part of the primary key.
B
Implement a custom versioning layer atop Delta tables that tracks changes in an external system for faster version retrieval.
C
Leverage Delta Lake‘s time travel feature, partitioning data by change date to optimize retrieval of specific versions.
D
Use a combination of materialized views and Delta Lake‘s event log to reconstruct historical states efficiently.
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