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MSAS: Analysis Services Aggregations
MSAS: Analysis Services Aggregations - Page 2
MSAS: Analysis Services Aggregations - Page 3MSAS: Analysis Services Aggregations
Cells store the value at the intersection of dimension coordinates. Whenever a query is made on the data, the results have to be fetched from the various locations of cells on the multidimensional structure, affecting response time. Aggregations consist of all the possible combinations of one level from each dimension in the cube. This makes query response time optimal.
However storage and processing time required for aggregations can be considerable. The storage requirements are defined by the number of dimensions, measures, levels and members in the dimension. The tradeoff is between storage requirements and the percentage of possible aggregations that are to be precalculated. If no aggregations are precalculated, storage only for the base data is required. Query response time will also be slow because base data will have to be worked upon each time a query is made. When aggregations are precalculated, other aggregations can quickly be computed from the existing aggregations. This impacts on query response time positively but on storage space negatively.
The Storage Design Wizard(see above)and the Usage Based Optimization Wizard (see below) enable the adjustment of aggregation design for a cube. The former provides options for specifying storage and percentage constraints to an algorithm that helps achieve a satisfactory tradeoff between query response time and storage requirements. The latter assists in aggregation design by analyzing queries that have been submitted by clients and refining the aggregation design accordingly.
Though aggregations are designed using the above said wizards, they get created only when the cube is processed. If the structure of the cube changes subsequent to creating the aggregation and processing the cube, the aggregations will have to be redesigned and the cube processed again.
In the object hierarchy aggregations are subordinate to a specific partition of a cube. If the cube contains only one partition, then the aggregations will be considered to be subordinate to the cube. It is because of this, that the above two wizards will require the selection of a partition if they are run on a multiple partition cube.
The Local cube partition’s aggregations are stored locally if the storage mode is MOLAP or HOLAP, in a subfolder of the Data folder of the Analysis server on which the partition is defined. If the partition was created on a remote Analysis server, then, the aggregations are stored remotely in MOLAP or HOLAP storage modes. In ROLAP storage mode, whether local or remote the partitions aggregations are stored in dedicated tables or indexed views in the database specified in the partition. We will learn more about how aggregations are stored in partitions in the lesson “Managing Partitions”
When programming with Decision Support Objects (DSO), the class type associated with aggregations is clsAggregation.
Managing aggregations in a Dimension
In situations where one or more users of a group need to have access to a dimension that is not required by other members of a group, Analysis services gives the user an option of controlling the way the aggregations of the dimension enter the pool of aggregations. The aggregation options Top Level Only and Bottom Level only can be set in such circumstances. Setting the Top Level only option results in effectively removing the dimension aggregations from the pool. As long as the user does not traverse the hierarchy of the dimension, the values of the dimension will be All Level. and responses for the users not requiring the dimension will be fast.
The Bottom Level only flag has the opposite effect. It prevents the aggregations for a dimension above the lowest level of detail. All users will be forced to pay a performance penalty even when they do not use the dimension.
Aggregation usage property can be set to Custom. This allows the user to disable or enable specific levels within the dimension. Manual control of dimension aggregations is not very efficient. Setting the usage control flags merely controls how levels from the dimension will enter the available pool for consideration by one of the Storage design wizards. Changing the setting has no effect until the wizard is run for designing new aggregations for a cube.
Analysis Services Training
- MSAS - Browsing the Dependency Network
- MSAS - Building a Relational Decision Tree Model
- MSAS - Introduction to Data Mining
- MSAS - Applying security to a Dimension
- Tutorial 65: MSAS - Managing Cube Roles
- MSAS - Understanding Database Roles
- MSAS - Securing User Authentication
- MSAS - Introducing Analysis Services Security
- MSAS - Writebacks
- MSAS - Defining and Creating Drillthrough
- MSAS - Defining and Creating Auctions
- MSAS - Creating and Maintaining Calculated Members in Virtual Cubes
- MSAS - Building a Virtual Cube
- MSAS - Understanding Virtual Cubes
- MSAS - Introducing Solve Order
- MSAS - Implementing Calculations Using MDX Part 2
- MSAS - Implementing Calculations Using MDX Part 1
- MSAS - Merging Partitions
- MSAS - Introduction and Managing Partitions
- MSAS - Troubleshooting Cube Processing
- MSAS - Optimizing Cube Processing
- MSAS - Processing Dimensions and Cubes
- MSAS - Introducing Dimension and Cube Processing
- MSAS: Optimization Tuning Part 2
- MSAS: Optimization Tuning Part 1
- MSAS: Usage-Based Optimization
- MSAS: Analysis Services Aggregations
- MSAS: The Storage Design Wizard
- MSAS: Analysis Server Cube Storage
- MSAS: Defining Cube Properties
- MSAS: Introduction and Working with Measures
- MSAS: Introduction and Working with Cubes
- MSAS: Virtual Dimensions
- MSAS: Introducing Member Properties
- MSAS: Creating Custom Rollups
- MSAS: Creating a Time Dimension
- MSAS: Understanding Hierarchies
- MSAS: Dimension Storage Modes and Levels
- MSAS: Working with Levels and Hierarchies
- MSAS: Working with Parent-Child Dimensions
- MSAS : Basics of Levels
- MSAS : Working with Standard Dimensions
- MSAS : Shared vs Private Dimensions
- Understanding Dimension Basics
- MSAS : Office 2000 OLAP Components
- MSAS : Client Architecture
- MSAS : Cube Storage options
- MSAS : Meta data Repository
- MSAS : Analysis services Tools for Extended Functionality
- MSAS : The Wizards
- MSAS : The Analysis Manager and Analysis Server
- MSAS : The Data warehousing framework of SQL Server 2000 - Part 2
- MSAS : The Data warehousing framework of SQL Server 2000 - Part 1
- MSAS : Microsoft Data Warehousing Overview
- MSAS : Browsing the Cube
- MSAS : Designing Storage and Processing the Cube
- MSAS : Building the Cube Part #3
- MSAS : Building the Cube Part #2
- MSAS : Building the Cube Part #1
- MSAS : Setting up the Database in Analysis Server
- MSAS : Preparing to Create the Cube
- MSAS : Introducing Analysis Manager Wizards
- Microsoft Analysis Services Installation
- MSAS - Applying OLAP Cubes
- Understanding OLAP Models
- Designing the Dimensional Model and Preparing the data for OLAP
- Design of the data warehouse: Kimball Vs Inmon
- Defining OLAP Solutions and Data Warehouse design
- Microsoft Analysis Services Training
- Data Warehouse database and OLTP database
- Introduction to Data Warehousing







