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Best Practices for Analysis Services
Craig Utley
Solid Quality Mentors
CIOBriefings LLC © 2008

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Who Am I?
Craig Utley, Mentor with Solid Quality Mentors
Former SQL Server MVP and C# MVP
Consultant specializing in development with Microsoft technologies and data warehousing
Published author of books, whitepapers, articles, and courseware
Operator of LearnMicrosoftBI.com
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3. My Business Intelligence Experience
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My Business Intelligence Experience
Worked on first data warehousing course from Microsoft (1998)
Working with BI in various forms for past 13 years
Former member on Microsoft’s SQL Customer Advisory Team (SQLCAT), focused on BI
Built warehouses or consulted on BI projects in financial, healthcare, manufacturing, and CPG industries
Conference speaker and article author on BI topics
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Agenda
There are a number of areas in which best practices can fall
This talk will discuss best practices in the following areas:
Design – General
Design – Data Sources and DSVs
Design – Dimensions
Design – Measure Groups, Partitions, Aggregations
Processing
Server Settings
Querying/MDX
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General Design
Analysis Services 2005 and 2008 are extremely different from Analysis Services 2000
Upgrading Analysis Services 2000 might work well on small, simple cubes
In almost all cases, expect to redesign the Analysis Services database to take advantage of new features
For larger projects, plan to have a hardware expert available who understands SAN, load balancing, and so forth
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Design – Data Sources
Data Sources should use Windows Authentication when connecting to SQL Server and then impersonate a domain account created for this purpose
Account should have the least privileges possible to get to the data
For SQL Server use the Microsoft OLE DB Provider for SQL Server or the SQL Server Native Client instead of the .NET Data Provider
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7. Design – Data Source Views
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Design – Data Source Views
In the Data Source View, create a new diagram for each fact table
This helps make each view look like its own star or snowflake schema
For simple calculations and concatenations, create new columns in the relational DW or new named calculations the DSV
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Demo
Data Sources and Data Source Views
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Design – Dimensions
There are a number of design issues related to dimensions, including
Attribute relationships
Attribute key columns and name column
Multilevel hierarchies and attribute hierarchies
Other areas
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10. Attribute Relationships
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Attribute Relationships
Attribute relationships tell the Analysis Services engine how attributes are related so that it can build aggregations and speed queries
Ensure that attribute relationships are created and created correctly
The visual designer in BIDS 2008 makes this much easier
Set the RelationshipType to Rigid when possible
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11. Attribute KeyColumns and NameColumn
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Attribute KeyColumns and NameColumn
Ensure that the KeyColumns is set to identify unique values
For example, a month value of 1 is insufficient if the dimension contains more than a single year
In this case, combine the Year and Month columns
Set the NameColumn to a column that makes it clear what is being shown
For example, instead of just a month value of 1, combine the month and year
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12. <Enter course name here>
Demo
Attribute Relationships
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13. Other Dimension Design Issues
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Other Dimension Design Issues
Hide attribute hierarchies for attributes added to a multilevel hierarchy
A dimension should contain no more than one non-aggregatable attribute
Use numeric key columns
Especially important for dimensions with more than 500,000 members
Parent-child dimensions should not have more than 500,000 members in the key attribute
Specify a dimension as type Time when possible
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14. Design – Measure Groups
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Design – Measure Groups
Avoid having multiple measure groups with the same granularity and dimensionality
Set IgnoreUnrelatedDimensions to False when possible to avoid repeating a value for all unrelated members
Don’t create a many-to-many relationship if the dimensions or intermediate fact table have more than one million members
Alternatives exist, check out Erik Veerman’s blog at
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Demo
Measure Groups
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Design – Aggregations
Rule of thumb is to create aggregations at 20% using Aggregation Design wizard
Then log queries during periods of normal activity and use the Usage Based Optimization wizard (UBO) to define better aggregations
Set approximate counts if there is too much data to let the wizard count the rows
When creating custom aggregations, do not create aggregations below the measure group’s granularity
Don’t create overlapping aggregations
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Demo
Aggregations
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Design – Partitions
Create partitions for larger data sets in order to speed up queries
Partition by common usage, such as by time
Partitioning by more than one criteria is acceptable, but ensure fact records do not appear in more than one partition
Cubes should have no more than 2,000 partitions with a maximum of 20,000,000 records each in SSAS 2005
Partition the relational warehouse fact table the same way as the cube
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Processing
Tweak the number of parallel tasks on the production server to see if a different value decreases processing time
Use ProcessData and ProcessIndex instead of ProcessFull to get a more consistent processing pattern
Use ASCMD to manipulate and process objects, especially on very large databases
Use the <Parallel></Parallel> block to process objects in parallel
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Server Settings
If running other apps or multiple instances of SSAS:
Move Memory/LowMemoryLimit below 75%
Move Memory/TotalMemoryLimit below 80%
Modify CoordinatorExecutionMode to increase parallelism
Negative numbers are the number of jobs per core
Set Threadpool\Query\MaxThreads to no more than 2X the number of cores
Set Threadpool\Process\MaxThreads to no more than 10X the number of cores
Use recommendations from the Microsoft SQL Server 2005/2008 Analysis Services Performance Guide
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Demo
Processing and Server Settings
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Querying Tips
Learn how to monitor queries in action
See Identifying and Resolving MDX Query Performance Bottlenecks in SQL Server 2005 Analysis Services
Make sure to understand the Threadpool\Query settings
See if data is coming from a cache, an aggregation, or a subcube query
In high usage scenarios it can be useful to adjust MemoryHeapType
Call PSS for support
Learn how to scale up and scale out
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MDX Tips
Set Non-empty behavior property on calculations where appropriate is SSAS 2005
Explicitly reference cells when possible
Products.Printers instead of Dimensions(2).Printers
Products.Printers instead of Products.CurrentMember
Move simple calculations (such as Measure1 * Measure2) from Calculations to the DSV
Understand what functions do cell by cell versus subspace computations
Learn how to use the Scope statement
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Scope vs. Nested IIF
CREATE MEMBER CURRENTCUBE.[MEASURES].[Foo] AS iif([Time].[Time Season].CurrentMember.Level IS [Time].[Time Season].[Day], null, iif([Time].[Time Season].CurrentMember.Level IS [Time].[Time Season].[Week], iif(isempty([Measures].[WTD Net Tot Sls]) or [MEasures].[WTD Net Tot Sls] = 0, null, [Measures].[TY Str Stk]/ [Measures].[WTD Net Tot Sls]), iif([Time].[Time Season].CurrentMember.Level is [Time].[Time Season].[Period], iif(isempty([Measures].[MTD Net Tot Sls]) or Measures].[MTD Net Tot Sls] = 0, null, [Measures].[TY Str Stk]/ [Measures].[MTD Net Tot Sls]), iif(isempty([Measures].[STD Net Tot Sls]) or [Measures].[STD Net Tot Sls] = 0, null, [Measures].[TY Str Stk]/[Measures].[STD Net Tot Sls] )
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25. Scope vs. Nested IIF Cont.
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Scope vs. Nested IIF Cont.
Create [Foo];
Scope [Foo];
[Time].[Time Season].[Week] =
IIF( [Measures].[WTD Net Tot Sls] = 0, null,
[Measures].[TY Str Stk] / [Measures].[WTD Net Tot Sls]);
[Time].[Time Season].[Period] =
IIF( [Measures].[MTD Net Tot Sls] = 0, null,
[Measures].[TY Str Stk] / [Measures].[MTD Net Tot Sls]);
[Time].[Time Season].[Season] =
IIF( [Measures].[STD Net Tot Sls] = 0, null,
[Measures].[TY Str Stk] / [Measures].[STD Net Tot Sls]);
End Scope;
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Summary
There are many best practices that must be applied during the design phase
Dimensions
Measure Groups
Data sources, and so forth
Processing can be tweaked through parallelism and memory adjustments
Querying can be tuned through proper MDX, memory adjustments, and partitioning
CIOBriefings LLC © 2008