Analysis Services Many-to-Many Dimensions: Query Performance Optimization Techniques

Language:
English
This best practices white paper discusses three many-to-many query performance optimization techniques, including how to implement them, and the performance testing results for each technique.
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    Version:

    1.0

    File Name:

    Many-to-ManyQryOptTech.docx

    SalesReasonMatrixLoad_SSIS.zip

    Date Published:

    3/29/2010

    File Size:

    691 KB

    176 KB

      Many-to-many dimension relationships in SQL Server 2005 Analysis Services (SSAS) enable you to easily model complex source schemas and provide great analytical capabilities. This capability frequently comes with a substantial cost in query performance due to the runtime join required by Analysis Services to resolve many-to-many queries. This best practices white paper discusses three many-to-many query performance optimization techniques, including how to implement them, and the performance testing results for each technique. It demonstrates that optimizing many-to-many relationships by compressing the common relationships between the many-to-many dimension and the data measure group, and then defining aggregations on both the data measure group and the intermediate measure group yields the best query performance. The results show dramatic improvement in the performance of many-to-many queries as the reduction in size of the intermediate measure group increases. Test results indicate that the greater the amount of compression, the greater the performance benefits—and that these benefits persist as additional fact data is added to the main fact table (and into the data measure group).
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      Windows 2000; Windows Server 2003; Windows Vista; Windows XP
      Microsoft Word
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