Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Using dynamic data masking with SUPER data type paths

Amazon Redshift supports attaching dynamic data masking policies to paths of SUPER type columns. For more information about the SUPER data type, see Ingesting and querying semistructured data in Amazon Redshift.

When attaching masking policies to paths of SUPER type columns, consider the following.

Examples

Attaching masking policies to SUPER paths

The following example attaches multiple masking policies onto multiple SUPER type paths in one column.

CREATE TABLE employees (
    col_person SUPER
);

INSERT INTO employees
VALUES
    (
        json_parse('
            {
                "name": {
                    "first": "John",
                    "last": "Doe"
                },
                "age": 25,
                "ssn": "111-22-3333",
                "company": "Company Inc."
            }
        ')
    ),
    (
        json_parse('
            {
                "name": {
                    "first": "Jane",
                    "last": "Appleseed"
                },
                "age": 34,
                "ssn": "444-55-7777",
                "company": "Organization Org."
            }
        ')
    )
;
GRANT ALL ON ALL TABLES IN SCHEMA "public" TO PUBLIC;

-- Create the masking policies.

-- This policy converts the given name to all uppercase letters.
CREATE MASKING POLICY mask_first_name
WITH(first_name TEXT)
USING ( UPPER(first_name) );

-- This policy replaces the given name with the fixed string 'XXXX'.
CREATE MASKING POLICY mask_last_name
WITH(last_name TEXT)
USING ( 'XXXX'::TEXT );

-- This policy rounds down the given age to the nearest 10.
CREATE MASKING POLICY mask_age
WITH(age INT)
USING ( (FLOOR(age::FLOAT / 10) * 10)::INT );

-- This policy converts the first five digits of the given SSN to 'XXX-XX'.
CREATE MASKING POLICY mask_ssn
WITH(ssn TEXT)
USING ( 'XXX-XX-'::TEXT || SUBSTRING(ssn::TEXT FROM 8 FOR 4) );

-- Attach the masking policies to the employees table.
ATTACH MASKING POLICY mask_first_name
ON employees(col_person.name.first)
TO PUBLIC;

ATTACH MASKING POLICY mask_last_name
ON employees(col_person.name.last)
TO PUBLIC;

ATTACH MASKING POLICY mask_age
ON employees(col_person.age)
TO PUBLIC;

ATTACH MASKING POLICY mask_ssn
ON employees(col_person.ssn)
TO PUBLIC;

-- Verify that your masking policies are attached.
SELECT
    policy_name,
    TABLE_NAME,
    priority,
    input_columns,
    output_columns
FROM
    svv_attached_masking_policy;

   policy_name   | table_name | priority |           input_columns           |          output_columns
-----------------+------------+----------+-----------------------------------+-----------------------------------
 mask_age        | employees  |        0 | ["col_person.\"age\""]            | ["col_person.\"age\""]
 mask_first_name | employees  |        0 | ["col_person.\"name\".\"first\""] | ["col_person.\"name\".\"first\""]
 mask_last_name  | employees  |        0 | ["col_person.\"name\".\"last\""]  | ["col_person.\"name\".\"last\""]
 mask_ssn        | employees  |        0 | ["col_person.\"ssn\""]            | ["col_person.\"ssn\""]
(4 rows)

-- Observe the masking policies taking effect.
SELECT col_person FROM employees ORDER BY col_person.age;

-- This result is formatted for ease of reading.
         col_person
--------------------------------
{
    "name": {
        "first": "JOHN",
        "last": "XXXX"
    },
    "age": 20,
    "ssn": "XXX-XX-3333",
    "company": "Company Inc."
}
{
    "name": {
        "first": "JANE",
        "last": "XXXX"
    },
    "age": 30,
    "ssn": "XXX-XX-7777",
    "company": "Organization Org."
}

Following are some examples of invalid masking policy attachments to SUPER paths.

-- This attachment fails because there is already a policy
-- with equal priority attached to employees.name.last, which is
-- on the same SUPER path as employees.name.
ATTACH MASKING POLICY mask_ssn
ON employees(col_person.name)
TO PUBLIC;
ERROR:  DDM policy "mask_last_name" is already attached on relation "employees" column "col_person."name"."last"" with same priority
               
-- Create a masking policy that masks DATETIME objects.
CREATE MASKING POLICY mask_date
WITH(INPUT DATETIME)
USING ( INPUT );
               
-- This attachment fails because SUPER type columns can't contain DATETIME objects.
ATTACH MASKING POLICY mask_date
ON employees(col_person.company)
TO PUBLIC;
ERROR:  cannot attach masking policy for output of type "timestamp without time zone" to column "col_person."company"" of type "super

Following is an example of attaching a masking policy to a SUPER path that doesn’t exist. By default, Amazon Redshift will resolve the path to NULL.

ATTACH MASKING POLICY mask_first_name
ON employees(col_person.not_exists)
TO PUBLIC;

SELECT col_person FROM employees LIMIT 1;

-- This result is formatted for ease of reading.
         col_person
-----------------------------------
{
    "name": {
        "first": "JOHN",
        "last": "XXXX"
    },
    "age": 20,
    "ssn": "XXX-XX-3333",
    "company": "Company Inc.",
    "not_exists": null
}