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
SVV_MV_DEPENDENCY
The SVV_MV_DEPENDENCY table shows the dependencies of materialized views on other materialized views within Amazon Redshift.
For more information about materialized views, see Materialized views in Amazon Redshift.
SVV_MV_DEPENDENCY is visible to all users. Superusers can see all rows; regular users can see only their own data. For more information, see Visibility of data in system tables and views.
Table columns
Column name | Data type | Description |
---|---|---|
database_name | char(128) | The database that contains the specified materialized view. |
schema_name | char(128) | The schema of the materialized view. |
name | char(128) | The name of the materialized view. |
dependent_database_name | char(128) | The materialized view database on which this materialized view depends. |
dependent_schema_name | char(128) | The materialized view schema on which this materialized view depends. |
dependent_name | char(128) | The name of the materialized view on which this materialized view depends. |
Sample query
The following query returns an output row that indicates that the materialized
view mv_over_foo
uses the materialized view mv_foo
in its
definition as a
dependency.
CREATE SCHEMA test_ivm_setup; CREATE TABLE test_ivm_setup.foo(a INT); CREATE MATERIALIZED VIEW test_ivm_setup.mv_foo AS SELECT * FROM test_ivm_setup.foo; CREATE MATERIALIZED VIEW test_ivm_setup.mv_over_foo AS SELECT * FROM test_ivm_setup.mv_foo; SELECT * FROM svv_mv_dependency; database_name | schema_name | name | dependent_database_name | dependent_schema_name | dependent_name ---------------+----------------------+-------------+-------------------------+---------------------------+---------- dev | test_ivm_setup | mv_over_foo | dev | test_ivm_setup | mv_foo