Book Image

Expert Cube Development with SSAS Multidimensional Models

By : Alberto Ferrari, Marco Russon, Chris Webb
Book Image

Expert Cube Development with SSAS Multidimensional Models

By: Alberto Ferrari, Marco Russon, Chris Webb

Overview of this book

Table of Contents (19 chapters)
Expert Cube Development with SSAS Multidimensional Models
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Caching


We've already seen how Analysis Services can cache the values returned in the cells of a query, and how this can have a significant impact on the performance of a query. Both the Formula Engine and the Storage Engine can cache data, but may not be able to do so in all circumstances; similarly, although Analysis Services can share the contents of the cache between users there are several situations where it is unable to do so. Given that in most cubes there will be a lot of overlap in the data that users are querying, caching is a very important factor in the overall performance of the cube and as a result ensuring that as much caching as possible is taking place is a good idea.

Formula cache scopes

There are three different cache 'contexts' within the Formula Engine, which relate to how long data can be stored within the cache and how that data can be shared between users:

  • Query Context: This means that the results of calculations can only be cached for the lifetime of a single query...