Analysis-Services/AsPartitionProcessing
2016-12-01 19:25:57 -08:00
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AsPartitionProcessing AsPartitionProcessing 2016-12-01 19:25:57 -08:00
AsPartitionProcessing.AdventureWorks AsPartitionProcessing 2016-12-01 19:25:57 -08:00
AsPartitionProcessing.SampleClient AsPartitionProcessing 2016-12-01 19:25:57 -08:00
AdventureWorksDW.bak AsPartitionProcessing 2016-12-01 19:25:57 -08:00
AsPartitionProcessing.sln AsPartitionProcessing 2016-12-01 19:25:57 -08:00
Automated Partition Management for Analysis Services Tabular Models.docx AsPartitionProcessing 2016-12-01 19:25:57 -08:00
Automated Partition Management for Analysis Services Tabular Models.pdf AsPartitionProcessing 2016-12-01 19:25:57 -08:00
CreateDatabaseObjects.sql AsPartitionProcessing 2016-12-01 19:25:57 -08:00
README.md AsPartitionProcessing 2016-12-01 19:25:57 -08:00
SampleConfiguration.sql AsPartitionProcessing 2016-12-01 19:25:57 -08:00

Microsoft BI technical whitepaper: Automated Partition Management for Analysis Services Tabular Models

Analysis Services tabular models can store data in a highly-compressed, in-memory cache for optimized query performance. This provides fast user interactivity over large data sets. Large datasets normally require table partitioning to accelerate and optimize the data-load process. Partitioning enables incremental loads, increases parallelization, and reduces memory consumption. The Tabular Object Model (TOM) serves as an API to create and manage partitions. Model Compatibility Level 1200 or above is required.

The AsPartitionProcessing TOM code sample is

  • Intended to be generic and configuration driven requiring minimal code changes.
  • Works for both Azure Analysis Services and SQL Server Analysis Services tabular models.
  • Can be leveraged in many ways including from an SSIS script task, Azure Functions and others.