In this article, we will explore another tool that MSAS
offers for the enhancement of cube processing, the Optimize Schema option.
Optimize Schema attempts to identify unnecessary joins between our fact and
dimension tables, and then to remove them. In many cases, the tool works
effectively to accomplish this, leading to a significant reduction in a cube’s
processing time. Elimination of the joins means more rapid resolution of MSAS’
queries to the relational database, upon which our cube is dependent as a data
source. This, in turn, means that data is pulled into Analysis Services in less
time, contributing to a more rapid cube build overall.
The operation of the Optimize
Schema option takes advantage of a common circumstance within the construction
of many star or snowflake schemas: the foreign key that serves as the basis of
a join between the fact table and a given dimension table is identical to the
member key itself. When this is the case, MSAS can eliminate the join, and
source the member key directly from the fact table, instead of relying upon a
join to the dimension table to obtain the key.
In this article, we will examine the use of Optimize
Schema in making our cubes process faster. To accomplish this objective, we
will:
- Overview the Optimize Schema option;
- Create a copy of the Warehouse sample cube for use
in our practice session;
- Prepare the cube copy further by processing;
- Discuss the Member Key Column property, and
examine existing settings within our practice cube;
- Discuss possible considerations in determining the
appropriateness of the use of the Optimize Schema option in our respective
business environments;
- Perform a practice exercise within which we employ
the Optimize Schema option;
- Examine some of the effects of using Optimize
Schema.
Read the Article ...
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Synopsis:
Simplify an Analysis Services cube schema
with point-and-click simplicity, eliminating joins between dimension and
fact tables.
MSAS Architect
Bill Pearson
leads
a hands-on introduction to using this option to significantly reduce cube
processing time.
Concepts:
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Analysis Services
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OLAP
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Cube
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MSSQL Server
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MDX
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Optimize
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Derived
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Schema
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Performance
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Member
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Key
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Column
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Join
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Editor
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Dimension
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Property
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Query
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Processing
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Calculated Member
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Property
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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.
Optimize, Schema, Performance, Member, Key, Column, Join,
Cube, Editor, Dimension, Analysis, Services, MSAS, Property, Query, Processing,
MDX, Cube, design, Calculated, Member, Property, Query, processing, Performance,
Editor, MDX, MSSQL, Server, Analysis, Services, optimization
All Contents Copyright Island Technologies Inc.
®
Island Technologies® and Island Technologies Inc.®
are registered trademarks of Island Technologies
Inc., protected in the United States and other countries. For information,
contact
Island.
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