MDX Essentials: Enhancing CROSSJOIN() with Calculated Members

About the Series …

This article is a member of the series, MDX Essentials.
The series is designed to provide hands-on application of the fundamentals of
the Multidimensional Expressions (MDX) language, with each tutorial
progressively adding features designed to meet specific real-world needs.

For more information about the series in general, as well as
the software and systems requirements for getting the most out of the lessons
included, please see my first article, MDX at
First Glance: Introduction to MDX Essentials

Note: Service Pack 3 updates are assumed for MSSQL
Server 2000
, MSSQL Server 2000 Analysis Services, and the related Books
and Samples.


an earlier article, The
CROSSJOIN() Function: Breaking Bottlenecks
, we examined the use of CROSSJOIN(), and
factors that can render this otherwise powerful function suboptimal within our
queries. We discussed a business need as defined by a hypothetical group of
information consumers, in which we were asked to tune an MDX query for more
optimal performance. Our focus centered upon enhancing query performance when using CROSSJOIN()
in medium- to
large-sized data sets. After discussing how CROSSJOIN() works in
general, and pointing out the way in which its operations can result in
crippling performance overhead, we exposed approaches to mitigating that
overhead within practice exercises designed to reinforce the concepts.

We learned that using NONEMPTYCROSSJOIN()
is, by far, the most effective avenue to minimizing the bottlenecks that plague
standard CROSSJOINS() within challenging cube scenarios. We examined
two approaches to using NONEMPTYCROSSJOIN() in achieving our ends,
finding refinements in the second approach, where we employed the optional set
parameter in the function, to provide more efficiency than the first
(which, even in its "vanilla" context, had demonstrated its power to
enhance performance dramatically). We noted, however, a prevailing concern
amid all this success: NONEMPTYCROSSJOIN() filters out calculated members, and so it is
not useful in a scenario where calculated members are to be returned.

In this article, we will examine the enhancement of queries
using CROSSJOIN() where calculated members are, indeed, to be returned.
We will begin with a simple, but intensive, CROSSJOIN() scenario,
reviewing how CROSSJOIN()
performance can become an issue where larger sized data sets are involved. We
will then undertake a multiple-step practice example, which will initially help
us to gain an understanding of the issues encountered with calculated
. We will attempt the approach to minimizing performance overhead
that we used in The CROSSJOIN() Function: Breaking Bottlenecks, where we met with a simpler
scenario that did not involve calculated members. We will then provide an
approach that provides palpable relief of the performance issues, while
returning a calculated member that we require to achieve our reporting and
analysis objectives.

To accomplish our examination of CROSSJOIN()
enhancement when calculated members are a factor, we will undertake the
following steps in this article:

  • Review CROSSJOIN()
    performance considerations that we introduced earlier;

  • Create a copy of the Warehouse
    sample cube for use in our practice exercise;

  • Add a calculated member
    to a dimension in the clone cube for consideration within our article;

  • Prepare the cube further by

  • Examine an
    instance of suboptimal query performance that we determine to be due to the
    resource-intensive use of CROSSJOIN(), highlighting factors that cause
    performance degradation;

  • Demonstrate
    issues inherent in the attempt to enhance a suboptimal CROSSJOIN() scenario by substituting NONEMPTYCROSSJOIN(),
    when calculated members need to be retrieved;

  • Provide an
    approach to enhancement of the CROSSJOIN() scenario
    with concomitant return of calculated members, using the GENERATE() function;

  • Explain the results we obtain from the steps we take to
    accomplish the solution.
William Pearson
William Pearson
Bill has been working with computers since before becoming a "big eight" CPA, after which he carried his growing information systems knowledge into management accounting, internal auditing, and various capacities of controllership. Bill entered the world of databases and financial systems when he became a consultant for CODA-Financials, a U.K. - based software company that hired only CPA's as application consultants to implement and maintain its integrated financial database - one of the most conceptually powerful, even in his current assessment, to have emerged. At CODA Bill deployed financial databases and business intelligence systems for many global clients. Working with SQL Server, Oracle, Sybase and Informix, and focusing on MSSQL Server, Bill created Island Technologies Inc. in 1997, and has developed a large and diverse customer base over the years since. Bill's background as a CPA, Internal Auditor and Management Accountant enable him to provide value to clients as a liaison between Accounting / Finance and Information Services. Moreover, as a Certified Information Technology Professional (CITP) - a Certified Public Accountant recognized for his or her unique ability to provide business insight by leveraging knowledge of information relationships and supporting technologies - Bill offers his clients the CPA's perspective and ability to understand the complicated business implications and risks associated with technology. From this perspective, he helps them to effectively manage information while ensuring the data's reliability, security, accessibility and relevance. Bill has implemented enterprise business intelligence systems over the years for many Fortune 500 companies, focusing his practice (since the advent of MSSQL Server 2000) upon the integrated Microsoft business intelligence solution. He leverages his years of experience with other enterprise OLAP and reporting applications (Cognos, Business Objects, Crystal, and others) in regular conversions of these once-dominant applications to the Microsoft BI stack. Bill believes it is easier to teach technical skills to people with non-technical training than vice-versa, and he constantly seeks ways to graft new technology into the Accounting and Finance arenas. Bill was awarded Microsoft SQL Server MVP in 2009. Hobbies include advanced literature studies and occasional lectures, with recent concentration upon the works of William Faulkner, Henry James, Marcel Proust, James Joyce, Honoré de Balzac, and Charles Dickens. Other long-time interests have included the exploration of generative music sourced from database architecture.
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