Processing a Cube

This topic describes how to process a cube in SQL Server Analysis Services (SSAS). Cube processing is the operation that loads data into the cube and its related objects (dimensions, measure groups, partitions, etc.) from the data sources. Understanding cube processing is crucial for maintaining data freshness and ensuring that users access the most up-to-date information.

Overview of Cube Processing

Cube processing involves several stages:

Processing Dimensions: Dimensions are processed first. This involves reading dimension data from the source, creating dimension tables, and populating attribute hierarchies.
Processing Fact Tables: Fact table data is read from the data source.
Processing Measures and Aggregations: Based on the processed dimension data and fact data, measures are calculated, and aggregations are built to optimize query performance.
Processing MOLAP/ROLAP/HOLAP: The storage mode (MOLAP, ROLAP, HOLAP) dictates how the processed data is stored and accessed.

Methods for Processing a Cube

You can process a cube using several methods:

1. SQL Server Management Studio (SSMS)

SSMS provides a graphical interface for managing and processing SSAS objects.

Connect to your Analysis Services instance in SSMS.
In Object Explorer, expand the database containing your cube.
Expand the "Cubes" folder.
Right-click the cube you want to process and select "Process...".
In the "Cube Processing" dialog box, select the objects you want to process (the entire cube, specific partitions, or dimensions).
Choose the processing type:

Process Full: Rebuilds the entire cube, including dimensions, measure groups, and partitions. This is the most thorough but time-consuming option.
Process Default: Processes only the objects that have changed since the last process. This is generally the recommended option for regular processing.
Process Add: Adds new data to existing partitions. Useful for incremental loads.
Process Recalc: Recalculates aggregations without reprocessing the underlying data.

Click "OK" to start the processing operation.

2. SQL Server Data Tools (SSDT)

When you deploy a solution from SSDT, you have the option to process the deployed objects.

In Visual Studio with Analysis Services projects, right-click the SSAS project.
Select "Deploy Solution".
In the "Deployment Wizard", on the "Specify Deployment Options" page, you can choose to "Process affected objects" or "Process all objects".

3. XMLA (XML for Analysis) Scripts

You can use XMLA scripts for programmatic processing, often used in automated ETL processes.

Here's a basic XMLA script to process a cube fully:

                
<?xml version="1.0" encoding="utf-8"?>
<Batch xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
  <Alter ObjectID="[YourCubeName]">
    <ObjectDefinition>
      <Cube xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
        <Name>[YourCubeName]</Name>
        <ddl100_100:Processing>ProcessFull</ddl100_100:Processing>
      </Cube>
    </ObjectDefinition>
  </Alter>
</Batch>
                
            

Replace [YourCubeName] with the actual name of your cube. You can execute XMLA scripts using SSMS or programmatically via AMO (Analysis Management Objects).

4. AMO (Analysis Management Objects)

AMO provides a .NET API for managing SSAS objects, including processing. This allows for advanced automation and integration with custom applications.

Example C# snippet:

                
using Microsoft.AnalysisServices.Tabular; // For Tabular, adjust for Multidimensional

// For Multidimensional
using Microsoft.AnalysisServices;

// ...

string connectionString = "Provider=MSOLAP;Data Source=YourServerName;Initial Catalog=YourDatabaseName;";
Microsoft.AnalysisServices.Server server = new Microsoft.AnalysisServices.Server();
server.Connect(connectionString);

Database db = server.Databases.GetByName("YourDatabaseName");
Cube cube = db.Cubes.GetByName("YourCubeName");

cube.Process(ProcessType.ProcessFull); // Or ProcessType.ProcessDefault

Note: The AMO API differs slightly between Tabular and Multidimensional models. The example above is conceptual for Multidimensional.

Processing Types Explained

Process Full: Clears all data from the cube and its related objects and then repopulates them. This is the most comprehensive but also the slowest. Use when significant structural changes have occurred or to ensure a completely fresh state.
Process Default: Processes only objects that have been modified since the last processing operation. SSAS intelligently determines what needs to be reprocessed. This is the most common choice for scheduled full refreshes.
Process Add: Appends new data to existing partitions. This is suitable for incremental data loads where you don't want to lose historical data already processed.
Process Data: Reprocesses only the data for measures and aggregations. Dimensions are not affected.
Process Index: Rebuilds internal structures (like hash tables) to optimize query performance. Useful if query performance degrades over time.
Process Structure: Reprocesses the structure of the cube but not the data. Useful for structural changes that don't involve new data.
Process Recalc: Recalculates all aggregations based on existing data without reprocessing the data itself.

Note

When processing dimensions separately, ensure that dimensions are processed before the cube that uses them, especially if you are using Process Default for the cube.

Best Practices for Cube Processing

Schedule Processing: Automate your cube processing using SQL Server Agent jobs or other scheduling tools.
Incremental Loading: Where possible, implement incremental loading for dimensions and fact data to reduce processing time.
Processing Order: Always process dimensions before processing the cube they belong to. If processing individual partitions, ensure related dimensions are processed first.
Monitor Performance: Regularly monitor processing times and resource utilization. Adjust processing types and schedules as needed.
Error Handling: Implement robust error handling and notification mechanisms for your processing jobs.
Use Process Default: For routine refreshes, Process Default is usually the most efficient option.
Process Full for Major Changes: Use Process Full only when necessary, such as after significant schema changes or when data corruption is suspected.

Tip

Consider processing partitions individually if only a subset of your data needs to be refreshed. This can significantly reduce processing time.

Troubleshooting Common Processing Issues

Data Source Connectivity: Ensure the SSAS service account has the necessary permissions to access all data sources.
Data Type Mismatches: Verify that data types in your source tables are compatible with the SSAS cube definition.
Key Violations: Check for duplicate keys in dimension tables or missing foreign keys in fact tables.
Locking Issues: Long-running queries or other operations on the Analysis Services server can sometimes block processing.

Warning

Processing a cube can consume significant server resources (CPU, memory, I/O). Schedule processing during off-peak hours to minimize impact on users.

By effectively managing and optimizing cube processing, you ensure that your business intelligence solutions deliver timely and accurate insights to your users.