Explanation:
The correct answer uses the is_member('compliance') function within a CASE statement to check if the current user is a member of the 'compliance' group. If true, the name column is displayed; otherwise, an empty string is returned, effectively restricting access. This approach correctly implements dynamic access control with valid syntax.
member = 'compliance', which is invalid syntax since member is a function, not a variable.name(IF 'compliance' in member), which Databricks SQL does not support.CREATE VIEW policy_view("name": "compliance") AS, which is not a valid method for specifying column-level access control in Databricks.Ultimate access to all questions.
A data engineer is tasked with restricting access to the name column in a dynamic view definition to only the compliance team. The original view is defined as:
CREATE VIEW policy_view AS
SELECT name, policy_id, age
FROM policy
CREATE VIEW policy_view AS
SELECT name, policy_id, age
FROM policy
Which SQL query correctly implements this access restriction?
A
CREATE OR REPLACE VIEW policy_view AS
SELECT
CASE
WHEN is_member('compliance') THEN name
ELSE ''
END AS name,
policy_id,
age
FROM policy;
CREATE OR REPLACE VIEW policy_view AS
SELECT
CASE
WHEN is_member('compliance') THEN name
ELSE ''
END AS name,
policy_id,
age
FROM policy;
B
CREATE VIEW policy_view AS
SELECT
CASE WHEN
member = 'compliance' THEN name
ELSE ''
END AS name,
policy_id,
age
FROM policy
CREATE VIEW policy_view AS
SELECT
CASE WHEN
member = 'compliance' THEN name
ELSE ''
END AS name,
policy_id,
age
FROM policy
C
CREATE VIEW policy_view AS
SELECT name(IF 'compliance' in member), policy_id, age
FROM policy
CREATE VIEW policy_view AS
SELECT name(IF 'compliance' in member), policy_id, age
FROM policy
D
CREATE VIEW policy_view("name": "compliance") AS
SELECT name, policy_id, age
FROM policy
CREATE VIEW policy_view("name": "compliance") AS
SELECT name, policy_id, age
FROM policy
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