Redshift materialized view limitations how to#
Redshift materialized view limitations update#

Query rewriting makes materialized views widely used: With this transparent rewriting, materialized views can be added or deleted in the same way as an index, without affecting existing SQL statements.

Redshift materialized view limitations how to#

An important issue in using materialized views to accelerate queries is how to automatically respond to queries by materialized views systematically and automatically. Query Rewriting Based on Materialized Viewsĭirectly querying a materialized view reduces the query processing time, but the query statement must be modified. This article describes the technical implementation of query acceleration by using materialized views from the query optimizer perspective. Materialized view utilization: Methods for query acceleration by using materialized views.

Redshift materialized view limitations update#

Materialized view maintenance: Reduce the cost and time to update materialized views.Materialized view selection: Select queries and tables to build a materialized view.To realize the potential of materialized views, three issues need to be solved: Materialized views are especially useful for queries that can be anticipated and repeatedly use the same subquery results. Thus, they greatly improve query processing time and reduce system load. Materialized views can eliminate the overhead of expensive joins and aggregations by responding to queries by pre-computed results. There are a large number of complex queries on large tables in the data warehouse, which can consume a lot of resources and time.

It, instead of building and computing datasets in runtime, pre-computes, stores, and optimizes data access when created, and automatically refreshes to ensure real-time data availability.įor data warehouses, the most important feature of materialized views is query acceleration. A Materialized view is the cache of views. A normal view provides ease-of-use and flexibility features, but it does not speed up data access. Background of Materialized ViewsĪ Materialized view is a special table that pre-calculates and stores the query results. Finally, several implementation methods of query rewriting and their advantages and disadvantages will be introduced. The second section will introduce the matching and rewriting process of query optimizers with materialized views. In this first section, a brief introduction to materialized views, as well as the purpose of query rewrite based on them, will be presented. This article describes the definition of materialized view and ways to rewrite queries based on it. In the database field, materialized view is a natural representation of precomputing and caching. In addition, caching allows fewer system resources to be consumed. For frequently repeated requests, if they can be answered by caching, it is much faster than computing for new results or reading from slower data storage. In the computing field, precomputing and caching are two common means to improving performance and reducing costs. By Yunxi from Alibaba Cloud Database OLAP Product Department