Technical Training
Analysis Services TrainingMSAS - Merging Partitions
To merge partitions with different storage designs, the partitions being merged must be edited to have the same storage design. The cubes must then be reprocessed before the merger is attempted. We will merge the Sales 97 partition back into the sales. Right click the Sales 97 partition and click Merge.
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The screen prompting the user to select the partition for merging appears as under. Since the cube only has two partitions the other partition is displayed in the Partition list box. Select the partition and click Merge.
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The partition merge begins and the process dialog box is displayed.
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Note that if the Sales partition had used a slice to limit the rows in the fact table whereas the Sales 97 partition used a filter to limit the rows of the fact table, the merger would result in the loss of the slice and the retention of the filter. After the merger the values of the cube will match the values in the fact table. On processing the cube the values of the filter will be excluded. The partition should be edited to remove the slice definition before merger, if the user wants to retain all the values.
Right click the partition Sales and click Process. Click the full process option and click Ok. Close the process log window, and browse Sales Partitioned cube data.
Now Right Click sales partition and navigate to the finish screen of the Wizard and click Advanced. Clear the contents of the filter statement box and Click design aggregations Later Option(to create a cube with no aggregations), select Process The Partition When Finished Check box and click Finish.
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Click Yes when informed about counting fact table rows and close the process log window. Then browse the cube.
Note that when partitions are defined users can specify a separate data source for each partition or the user can specify a different data slice for each partition or a different data filter for each partition. A combination is also possible.
While merging partitions that have different data sources the data source for the target partition is retained and that of the merged partition is discarded. Analysis services provides no means of combining the two fact tables. The combination must be done outside Analysis services.
When two partitions using filters are merged, Analysis combines the filters using the OR expression. When two partitions using slices are merged, Analysis services, behaves peculiarly if the two slices come from two different data sources—both slices are discarded. If the slices come from the same dimension the slice of the resulting cube becomes the lowest common parent.
Therefore, before merging partitions it is important to check the data sources, data slices and data filter specifications and also that of the resulting partition.
In this lesson we have learnt all about partitions, how to work with partition wizard to create partitions, use advanced settings to create filters and how to merge partitions. To learn more about ”Implementing Calculations using MDX” navigate to the next lesson of this series.
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











