A complete refresh occurs when the materialized view is initially defined as BUILD IMMEDIATE, unless the materialized view references a prebuilt table.For materialized views using BUILD DEFERRED, a complete refresh must be requested before it can be used for the first time.A complete refresh may be requested at any time during the life of any materialized view. Description. Starting from 9.5, Postgres supports Concurrent Refresh as stated here in the official documentation. 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. I have a very complex Oracle view based on other materialized views, regular views as well as some tables (I can't "fast refresh" it). However, since 9.5 I believe, there is a way to update a MV without having to regenerate all the data. The updated patch can be tested as such: > > CREATE ROLE bar LOGIN; > CREATE TABLE a (x int); > CREATE MATERIALIZED VIEW b AS SELECT * FROM a; > \c - bar > REFRESH MATERIALIZED VIEW b; > ERROR: must be owner of materialized view b > > I'm happy to generate the backpatches for it but wanted to receive feedback > first. I've also got a cron job refreshing the materialized view with refresh materialized view price_changes.Everything is working great. Take, for example, a view created on the pgbench dataset (scale 100, after ~150,000 transactions): postgres=# CREATE OR REPLACE VIEW account_balances AS SELECT a. REFRESH MATERIALIZED VIEW mymatview; The information about a materialized view in the PostgreSQL system catalogs is exactly the same as it is for a table or view. This is what I'm doing now. I've got a materialized view called price_changes used for some reporting. But it works for now. For large data sets, sometimes VIEW does not perform well because it runs the underlying query **every** time the VIEW is referenced. The upcoming version of Postgres is adding many basic things like the possibility to create, manage and refresh a materialized views. However, there are two preconditions that needs to be satisfied to do so: You must create an unique index on the materialized view; The unique index must include all the records of the materialized view. The old contents are discarded. The old contents are discarded. Most of the time, existing records in this view are based on a date and are "stable", with new record sets having new dates. However, materialized views in Postgres 9.3 have a severe limitation consisting in using an exclusive lock when refreshing it. One could create a PL/PGSQL function that uses these views to refresh all materialized views at once, but as this is a relatively rare command to execute that can take a long time to run, I figured it was best just to use these views to generate the code one needs to execute and then execute that code. Occasionally, I receive back-dates. I'd like to give users looking at the report a message "Data is fresh as of X". * Refreshing all materialized views. An OK solution using triggers. I'm looking at the PostgreSQL docs where: REFRESH MATERIALIZED VIEW completely replaces the contents of a materialized view. VIEW v. MATERIALIZED VIEW. Postgres 9.3 has introduced the first features related to materialized views. Unfortunately in such cases, only the latest query is of any relevance; all the previous queries consume processing time in vain to refresh … REFRESH MATERIALIZED VIEW completely replaces the contents of a materialized view. 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. (In the future, we're thinking of using an actual table for search instead of a materialized view, and updating individual relevant rows via triggers instead of refreshing an entire matview.) So for the parser, a materialized view is a relation, just like a table or a view. To execute this command you must be the owner of the materialized view. It's not exactly what I wanted because the trigger fires once per statement instead of once per transaction. Summary: this tutorial introduces you to PostgreSQL materialized views that allow you to store result of a query physically and update the data periodically.. In PostgreSQL view tutorial, you have learned that views are virtual tables which represent data of the underlying tables. Where: refresh materialized view a MV without having to regenerate all data... 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