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If you could automatically reduce your network resource load and simultaneously speed up query results, you would, wouldn’t you?. In fact, that might be a key focus of your job. Snowflake has you covered with a brand new generally available feature: Snowflake Materialized View(Snowflake MVs).
A materialized view (MV) is a database object, contains results of a query with data refreshed periodically. Therefore, these views are automatically and transparently maintained by Snowflake. A background service update materialized views once changes are made to the base table.
Refreshing service starts automatically , if main table modified.
select * from table(information_schema.materialized_view_refresh_history());There is some cost associated with refresh query.
Limitations and Restrictions:
Below are the limitations:
- Can query only a single table.
- Joins, including self-joins, are not supported.
In addition, A MV cannot include:
- UDFs (this limitation applies to all types of user-defined functions, including external functions).
- Window functions.
- HAVING clauses.
- ORDER BY clause.
- LIMIT clause.
- GROUP BY keys that are not within the SELECT list. All GROUP BY keys in a MV must be part of the SELECT list.
Older versions of MVs have their problems. For example, refreshing data periodically can lead to inconsistent or out-of-date results when you access MVs.
And beyond that, data manipulation language (DML) operations (for adding, deleting, and modifying data) traditionally experienced slow-downs when they used MVs.
Modernizes Materialized Views:
However, Snowflake now offers a new, modern approach to MV capabilities through a version that avoids the pain points of traditional approaches.
Snowflake MVs:
- Ensure optimal speed (no slowdowns)
- Deliver query results via MVs that are always current and consistent with the main data table
- Provide exceptional ease of use via a maintenance service that continuously runs and updates MVs in the background
Implementing Snowflake MVs enhances data performance by helping you filter data so you can perform resource-intensive operations and store the results, eliminating the need to continuously or frequently perform resource-intensive operations.
To prevent MVs from becoming out-of-date, Snowflake performs automatic background maintenance of MVs. When a base table changes, a background service automatically updates all MVs defined on the table.
Why creating a Materialized Views, Click here:
