Explanation:
Because the analyst is not a member of the "auditing" group, the SQL function is_member("auditing") evaluates to FALSE. The CASE statement in the WHERE clause then defaults to the ELSE condition: age >= 18.
This logic acts as a row-level filter. Only rows where the age is 18 or older satisfy the predicate and are included in the view's output. The selected columns (email, age, lifetimevalue) are returned with their original values for the surviving rows.
CASE statement in the SELECT clause) to turn values into NULL.CASE statement in the WHERE clause implements.Ultimate access to all questions.
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A data engineering team manages a Databricks environment where access is controlled via group-based Access Control Lists (ACLs). A table named user_lifetimevalue contains columns email (STRING), age (INT), and lifetimevalue (INT).
A view is defined as follows:
CREATE VIEW userltv_without_minors AS
SELECT email, age, lifetimevalue
FROM user_lifetimevalue
WHERE CASE WHEN is_member("auditing") THEN true ELSE age >= 18 END;
CREATE VIEW userltv_without_minors AS
SELECT email, age, lifetimevalue
FROM user_lifetimevalue
WHERE CASE WHEN is_member("auditing") THEN true ELSE age >= 18 END;
An analyst who is not a member of the "auditing" group executes the following query:
SELECT * FROM userltv_without_minors;
SELECT * FROM userltv_without_minors;
Based on the view definition and the analyst's group membership, which statement best describes the results returned?
A
All age values less than 18 will be returned as NULL, while other columns retain their original values from the underlying table.
B
The query will return all columns for records where age is 18 or older. Records for users under 18 will be excluded from the results.
C
The query will return all records and columns from the underlying table because the is_member function is only used for auditing logs, not row-level security.
D
The query will return all columns for records where age is strictly greater than 18. Records for users aged 18 and younger will be filtered out.
E
All values in the age column will be NULL for every record, while the email and lifetimevalue columns retain their original values.