Explanation:
Option A is correct because Delta Lake does not enforce foreign key constraints. While Databricks allows you to declare primary and foreign key relationships (with Unity Catalog and supported runtimes), these constraints are informational only and do not guarantee data integrity. As a result, enforcing referential integrity must be handled through application logic, ETL validation, or data quality checks, which can increase development effort.
ALTER TABLE.In Databricks, PK/FK constraints document relationships, they don’t enforce them. Understanding this distinction is critical for the certification exam.
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In the context of data modeling using Delta Lake on Azure Databricks, a data engineer is tasked with designing a solution that ensures data integrity across related tables without relying on application logic. The solution must be scalable, cost-effective, and comply with organizational data governance policies. Considering these constraints, which of the following approaches BEST demonstrates how to implement foreign key constraints in Delta Lake to maintain data integrity? Choose the correct option from the four provided.
A
Foreign key constraints are not supported in Delta Lake, so data integrity must be enforced through application logic, which may increase development time and complexity.
B
Creating a Delta Lake table with foreign key constraints requires integrating a third-party library or external system, potentially introducing additional costs and complexity.
C
Delta Lake supports foreign key constraints natively, which can be defined using the ALTER TABLE statement to ensure data integrity without external dependencies.
D
Foreign key constraints can be simulated in Delta Lake using a combination of MERGE INTO and DELETE statements, but this approach may not fully guarantee data integrity under all scenarios.