ALTER MASKING POLICY - Amazon Redshift
SyntaxParameters

Amazon Redshift will no longer support the creation of new Python UDFs starting November 1, 2025. If you would like to use Python UDFs, create the UDFs prior to that date. Existing Python UDFs will continue to function as normal. For more information, see the blog post .

ALTER MASKING POLICY

Alters an existing dynamic data masking policy. For more information on dynamic data masking, see Dynamic data masking.

Superusers and users or roles that have the sys:secadmin role can alter a masking policy.

Syntax

ALTER MASKING POLICY policy_name 
   USING (masking_expression);

Parameters

policy_name

The name of the masking policy. This must be the name of a masking policy that already exists in the database.

masking_expression

The SQL expression used to transform the target columns. It can be written using data manipulation functions such as String manipulation functions, or in conjunction with user-defined functions written in SQL, Python, or with AWS Lambda.

The expression must match the original expression's input columns and data types. For example, if the original masking policy's input columns were sample_1 FLOAT and sample_2 VARCHAR(10), you wouldn't be able to alter the masking policy to take a third column, or make the policy take a FLOAT and a BOOLEAN. If you use a constant as your masking expression, you must explicitly cast it to a type that matches the input type.

You must have the USAGE permission on any user-defined functions that you use in the masking expression.