Scripting Analysis Services Objects

Introduction to Scripting

Scripting in Analysis Services provides a powerful way to automate administrative tasks, deploy solutions, and manage your multidimensional and tabular models. By using scripting, you can reduce manual effort, ensure consistency, and integrate Analysis Services operations into larger workflows.

This section covers the core concepts and tools for scripting Analysis Services, enabling you to build efficient and robust management solutions.

Supported Scripting Languages

Analysis Services primarily supports the following scripting approaches:

• XML for Analysis (XMLA): A SOAP-based protocol used for communicating with Analysis Services. It's the fundamental language for sending commands and retrieving metadata.
• PowerShell: A powerful command-line shell and scripting language that can be used to automate tasks on Windows, including interacting with Analysis Services through its cmdlets and .NET Framework integration.
• AMO (Analysis Management Objects): A .NET Framework library that provides an object model for managing Analysis Services. It can be used from within PowerShell or other .NET applications.

Using XML for Analysis (XMLA)

XMLA is the native protocol for interacting with Analysis Services. You can send XMLA commands directly to the server to perform operations such as creating databases, processing objects, executing queries, and managing security.

Common XMLA Commands

Here are some examples of common XMLA commands:

• Creating a Database:

<Create xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
    <Object>
        <Database ID="NewDatabase" />
    </Object>
</Create>

• Processing a Cube:

<Execute xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
    <Command>
        <Process xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
            <Object>
                <DatabaseID>MyDatabase</DatabaseID>
                <CubeID>MyCube</CubeID>
            </Object>
            <Type>ProcessFull</Type>
        </Process>
    </Command>
    <PropertyList>
        <DataSourceInfo>Provider=MSOLAP;Data Source=localhost;</DataSourceInfo>
        <Catalog>MyDatabase</Catalog>
    </PropertyList>
</Execute>

You can execute XMLA commands using tools like SQL Server Management Studio (SSMS) or programmatically via AMO or ADOMD.NET.

PowerShell for Analysis Services

PowerShell is an excellent choice for automating Analysis Services management. It leverages the SqlServer module, which includes cmdlets for SQL Server, Analysis Services, and other SQL Server components.

Key PowerShell Cmdlets

• Invoke-Sqlcmd: Used to execute T-SQL or XMLA commands against SQL Server instances.
• New-Database, Remove-Database, Set-Database: For managing Analysis Services databases.
• Process-Database, Process-Cube, Process-Partition: For processing Analysis Services objects.
• Restore-Database, Backup-Database: For backup and restore operations.

Example: Processing a Database with PowerShell

Import-Module SqlServer

$serverName = "localhost"
$databaseName = "MyDatabase"

# Connect to the Analysis Services instance
$asServer = New-Object Microsoft.AnalysisServices.Tabular.TabularServer($serverName)

# Process the entire database
try {
    $asServer.Databases.GetByName($databaseName).Process(Microsoft.AnalysisServices.ProcessType.ProcessFull)
    Write-Host "Successfully processed database: $databaseName"
}
catch {
    Write-Error "Error processing database: $($_.Exception.Message)"
}

Common Scripting Tasks

Scripting is invaluable for a variety of Analysis Services operations:

• Automated Deployments: Script the deployment of new or updated Analysis Services projects.
• Scheduled Processing: Automate the nightly or periodic processing of cubes and partitions.
• Database Creation/Deletion: Script the setup and teardown of development or testing environments.
• Security Management: Automate the assignment of roles and permissions.
• Backup and Restore: Implement scheduled backup routines and disaster recovery procedures.
• Metadata Management: Script the retrieval and modification of cube metadata.

Best Practices for Scripting

• Version Control: Store your scripts in a version control system (e.g., Git).
• Parameterization: Use parameters for server names, database names, and other configurable values.
• Error Handling: Implement robust error handling and logging mechanisms.
• Idempotency: Design scripts so they can be run multiple times without causing unintended side effects.
• Modularity: Break down complex tasks into smaller, reusable script functions.
• Testing: Thoroughly test your scripts in a non-production environment before deploying them.