Amazon Redshift materialized views

Amazon Redshift materialized views do not automatically refresh when the underlying data changes. You need to manually refresh the materialized view to keep the data up to date.

How to Refresh a Materialized View

To refresh the data in a materialized view, you must run the following command:

REFRESH MATERIALIZED VIEW view_name;

This command updates the materialized view with the latest data from the underlying tables.

When to Refresh the Materialized View

You should refresh the materialized view:

• After the underlying tables have been updated (inserts, updates, or deletes).
• Before running any queries that rely on the most up-to-date data from the materialized view.

Automating the Refresh

While Redshift doesn’t support automatic refresh out of the box, you can automate the refresh process using one of the following options:

1. Scheduled Queries: Use Amazon Redshift’s SQL-based scheduling to run the REFRESH MATERIALIZED VIEW command at regular intervals. You can set up a schedule for refreshing views using AWS services like AWS Lambda or AWS EventBridge.
2. Triggers or ETL Jobs: If you’re using a pipeline or ETL process to load data into Redshift, you can trigger the refresh after each data load. This can be done by adding the refresh command to your ETL workflow.

Monitoring Materialized Views

You can use system tables like SVL_MV_REFRESH_STATUS to monitor the status of materialized views and check if they need to be refreshed:

SELECT * FROM SVL_MV_REFRESH_STATUS
WHERE mv_name = 'your_materialized_view';

This will show you the last refresh time and the status of the materialized view.

Summary:

• Redshift materialized views do not refresh automatically.
• You need to manually refresh them using the REFRESH MATERIALIZED VIEW command.
• You can automate the refresh using scheduled queries or by integrating it into your ETL workflow.