Databricks Data Engineer Associate Question 204
Single answerA data engineering team in your organization has created a SQL User-Defined Function (UDF) to standardize address formatting across datasets. They want to share this UDF with another team working on a different workspace within the same Databricks account. Based on Databricks' security model for sharing SQL UDFs, how should this be achieved?
- A
By granting access to the UDF's schema to the target team.
- B
By exporting the UDF as a JAR file and importing it into the target workspace.
- C
By using Unity Catalog to define the UDF and assigning appropriate permissions.
- D
By copying the SQL code of the UDF and manually recreating it in the target workspace.
Show answer and explanation
Correct answer: C
Explanation
In Databricks, SQL UDFs can be effectively shared across workspaces using Unity Catalog. Unity Catalog allows you to define UDFs centrally and manage their access through permissions. This ensures secure and consistent sharing of UDFs while adhering to governance policies, making it the recommended approach.
- A. Incorrect.
Granting access to the UDF's schema will not enable sharing of the UDF across workspaces; schemas are restricted to a single workspace.
- B. Incorrect.
While exporting the UDF as a JAR file could work for Python or Scala UDFs, SQL UDFs are defined and managed differently in Databricks and cannot be shared this way.
- C. Correct.
Unity Catalog provides a centralized governance model that supports sharing SQL UDFs across workspaces within the same account by defining them in a catalog and controlling access.
- D. Incorrect.
Manually copying and recreating the UDF in another workspace is not a recommended approach, as it introduces the risk of inconsistencies and is not aligned with Databricks' security and governance best practices.