Updating materialized view Free no singing in webcams
Cassandra performs a read repair to a materialized view only after updating the source table. I am java developer and not experienced with Oracle but I am trying to leverage Oracle to create some aggregate tables.The example code in this article assumes DB1 is the master instance and DB2 is the materialized view site.-- Normal CREATE MATERIALIZED VIEW view-name BUILD [IMMEDIATE | DEFERRED] REFRESH [FAST | COMPLETE | FORCE ] ON [COMMIT | DEMAND ]
CREATE MATERIALIZED VIEW dpc_level_mv BUILD IMMEDIATE REFRESH FAST ENABLE QUERY REWRITE AS SELECT DEPARTUREPOINTCODE, min(LEADINPRICE) AS MIN_LEADINPRICE, max(LEADINPRICE) AS MAX_LEADINPRICE, avg(LEADINPRICE) AS AVG_LEADINPRICE, count(*) AS COUNT FROM HSDCube_FACT GROUP BY DEPARTUREPOINTCODE The query is complex becuase of the aggregates, but the following web page seems to demonstrate such queries provided that certain conditions are met: Many of the examples seem more complex than mine. Without the aggregates the extra count field is not required. Thanks for the feedback, I thought count(*) would be sufficient, of course it is not as "leadinprice" could be null so result is not the same, I should think about that.
I was wondering if I was missing a parameter or option. So this also works: create materialized view dpc_level_mv build immediate refresh fast enable query rewrite as select departurepointcode, count(*) as count from hsdcube_fact fact group by departurepointcode If you have aggregates dependent on different expressions then they also each need to have their own count column.
As I am new to oracle I am a bit short-sighted when reading the docco.
If a materialized view is configured to refresh on commit, you should never need to manually refresh it, unless a rebuild is necessary.
Remember, refreshing on commit is a very intensive operation for volatile base tables.
A materialized view, or snapshot as they were previously known, is a table segment whose contents are periodically refreshed based on a query, either against a local or remote table.