For example, a row in a master table might be updated 10 times since the last refresh of a materialized view, but the result is still only one update of the corresponding row in the materialized view during the next refresh. If a view is being referenced at least twice before any updates occur, then the materialized view should provide superior performance. I will not show you the materialized view concepts, the Oracle Datawarehouse Guide is perfect for that. If possible, refresh should be performed after each type of data change (as shown earlier) rather than issuing only one refresh at the end. anyone able to tell me how often a materialized view is set to refresh with the following setting plz? Automatic fast refresh of materialized views The automatic fast refresh feature is completely new in Oracle, so you can refresh a snapshot with DBMS_JOB in a short interval according to the snapshot log. Unfortunately in such cases, only the latest query is of any relevance; all the previous queries consume processing time in vain to refresh … REFRESH FORCE: indicates that a fast refresh should be performed if possible, but if not, a complete refresh is performed. Even more optimal is the separation of INSERT and DELETE. ON COMMIT Refresh. However, as the "REFRESH MATERIALIZED VIEW" query takes at least several minutes, quite often such queries pile up in a queue, and they all execute one after the other. The frequency of this refresh can be configured to run on-demand or at regular time intervals. If materialized views are in a refresh group that is not refreshing often enough, then you can make the refresh interval shorter for the refresh group. With Oracle, it's possible to refresh automatically on the next COMMIT performed at the master table. REFRESH COMPLETE: uses a complete refresh by re-running the query in the materialized view. REFRESH MATERIALIZED VIEW completely replaces the contents of a materialized view. You can base your decision of whether to use a standard view or a materialized view on how often the input tables to the view are updated, versus how often the view is referenced in an SQL statement. In many cases, Amazon Redshift can perform an incremental refresh. REFRESH FORCE ON DEMAND START WITH sysdate+0 NEXT (round(sysdate) + 1/24) + 1. i think i read it as every hour but i'm not sure Therefore, whenever a transaction commits which has updated the tables on which a materialized view is defined, those changes are automatically reflected in the materialized view. Refresh materialized view. Refresh materialized views. In contrary of views, materialized views avoid executing the SQL query for every access by storing the result set of the query. If you refresh materialized views manually, then you might need to refresh them more often if materialized view logs are becoming too large. In an incremental refresh, Amazon Redshift quickly identifies the changes to the data in the base tables since the last refresh and updates the data in the materialized view.Incremental refresh is supported on the following SQL constructs used in the query when defining the materialized view: the materialized view log is newer than the last full refresh meaning - the log was created AFTER the materialized view was created/fully refreshed - meaning - the log might not have a record of every change needed to make the materialized view consistent. A materialized view can be refreshed automatically using the ON COMMIT method. If WITH DATA is specified (or defaults) the backing query is executed to provide the new data, and the materialized view is left in a scannable state. Description. See "Refreshing a Materialized View". When a master table is modified, the related materialized view becomes stale and a refresh is necessary to have the materialized view up to date. 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