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Related Articles
Introduction to SQL Server 2000 Analysis Services: Handling Time Dimensions
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MS SQL

February 14, 2005

Introduction to MSSQL Server 2000 Analysis Services: Manage Distinct Count with a Virtual Cube

By William Pearson

About the Series ...

This article is a member of the series Introduction to MSSQL Server 2000 Analysis Services. The series is designed to provide hands-on application of the fundamentals of MS SQL Server 2000 Analysis Services, with each installment progressively adding features and techniques designed to meet specific real - world needs. For more information on the series, as well as the hardware / software requirements to prepare for the exercises we will undertake, please see my initial article, Creating Our First Cube.

Note: Service Pack 3 updates are assumed for MSSQL Server 2000, MSSQL Server 2000 Analysis Services, and the related Books Online and Samples. Images are from a Windows 2003 Server environment, upon which I have also implemented MS Office 2003, but the steps performed in the articles, together with the views that result, will be quite similar within any environment that supports MSSQL Server 2000 and MSSQL Server 2000 Analysis Services ("Analysis Services" or "MSAS"). The same is generally true, except where differences are specifically noted, when MS Office 2000 and above are used in the environment, in cases where MS Office components are presented in the article.

Introduction

In this article, we will continue the exploration of distinct counts we began in our previous article, Distinct Count Basics: Two Perspectives. Having discussed why distinct counts are useful, and often required, within the design of robust analysis and reporting applications, we described some of the challenges that are inherent in distinct counts. We then undertook practice exercises to illustrate general solutions to meet example business requirements, providing an approach afforded us by the MSAS user interface, and then an alternative approach we enacted using MDX. Our stated purpose was to lay the framework for this and subsequent articles, where we will focus upon specific scenarios that occur commonly in the business environment, within which the optimal use of distinct counts can become a very real consideration.

In this article, we will examine one approach to the efficient use of DISTINCT COUNT within our applications: We will focus upon the optimization of DISTINCT COUNT through the isolation of the DISTINCT COUNT attributes into a separate cube, and show how this represents one of the more efficient approaches to optimizing the related functionality. To accomplish our objectives, we will undertake the following steps in this article:

  • Set the stage by providing a hypothetical business requirement;
  • Meet the requirement with an MDX query that contains DISTINCT COUNT;
  • Comment upon performance of the query in general;
  • Create a separate cube to house the DISTINCT COUNT attributes of our solution;
  • Combine the new DISTINCT COUNT cube with the previously existing cube, through the creation of a virtual cube in MSAS;
  • Create a new query, targeting the virtual cube as its source, to return a dataset identical to that returned by our initial query;
  • Comment upon performance gains in executing the new query upon the new cube combination.

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