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Power BI semantic models can store data in a highly compressed in-memory cache for optimized query performance, enabling fast user interactivity. The default size limit is 1 GB. With Fabric capacities, semantic models can exceed the default size limit if the Large semantic model storage format setting is enabled. When using the large storage format, the size limit is equal to the Fabric capacity size or the maximum size set by the capacity administrator. For Pro workspaces assigned to the Reserved Capacity for Pro Workspaces, the semantic model size limit is 1 GB.
The Large semantic model storage format setting can be enabled for all Fabric F SKUs, Premium P SKUs, Embedded A SKUs, with Premium Per User (PPU) and Pro workspaces assigned to Reserved Capacity for Pro Workspaces.
While required for semantic models to grow beyond 10 GB, enabling the Large semantic model storage format has other benefits. If you're planning to use XMLA-based tools for semantic model write operations, be sure to enable this setting, even for semantic models that you wouldn't necessarily characterize as a large semantic model because the large storage format can improve XMLA write performance. Semantic models in Pro workspaces do not support XMLA-based write operations.
Large semantic models in the service don't affect the Power BI Desktop model upload size, which is still limited to 10 GB. Instead, semantic models can grow beyond that limit in the service on refresh.
Important
Power BI Premium does support large semantic models. Enable the Large semantic model storage format option to use semantic models in Power BI Premium that are larger than the default limit.
Note
Large semantic models in Power BI Premium aren't available in the Power BI service for U.S. Government DoD customers. For more information about which features are available, and which aren't, see Power BI feature availability for U.S. Government customers.
Enable large semantic models
Steps here describe enabling large semantic models for a new model published to the service. For existing semantic models, only step 3 is necessary.
Create a model in Power BI Desktop. If your semantic model becomes larger and progressively consumes more memory, be sure to configure Incremental refresh.
Publish the model as a semantic model to the service.
In the service > semantic model > Settings, expand Large semantic model storage format, set the slider to On, and then select Apply.
Invoke a refresh to load historical data based on the incremental refresh policy. The first refresh could take a while to load the history. Subsequent refreshes should be faster, depending on your incremental refresh policy.
Set default storage format
In supported regions, all new semantic models created in a workspace assigned to a Premium capacity can have the large semantic model storage format enabled by default. If the region doesn't support large semantic models, the large semantic model storage format option described below is disabled. You can see which regions are supported in the region availability section.
In the workspace, select Settings > Premium.
In Default storage format, select Large semantic model storage format, and then select Save.
Enable with PowerShell
You can also enable large semantic model storage format by using PowerShell. You must have capacity admin and workspace admin privileges to run the PowerShell cmdlets.
Find the semantic model ID (GUID). On the Semantic models tab for the workspace, under the semantic model settings, you can see the ID in the URL.
From a PowerShell admin prompt, install the MicrosoftPowerBIMgmt module.
Install-Module -Name MicrosoftPowerBIMgmt
Run the following cmdlets to sign in and check the semantic model storage mode.
Login-PowerBIServiceAccount (Get-PowerBIDataset -Scope Organization -Id <Semantic model ID> -Include actualStorage).ActualStorage
The response should be the following. The storage mode is ABF (Analysis Services backup file), which is the default.
Id StorageMode -- ----------- <Semantic model ID> Abf
Run the following cmdlets to set the storage mode. It can take a few seconds to convert to Premium Files.
Set-PowerBIDataset -Id <Semantic model ID> -TargetStorageMode PremiumFiles (Get-PowerBIDataset -Scope Organization -Id <Semantic model ID> -Include actualStorage).ActualStorage
The response should be the following. The storage mode is now set to Premium Files.
Id StorageMode -- ----------- <Semantic model ID> PremiumFiles
You can check the status of semantic model conversions to and from Premium Files by using the Get-PowerBIWorkspaceMigrationStatus cmdlet.
Semantic model eviction
Semantic model eviction is a Premium feature that allows the sum of semantic model sizes to be significantly greater than the memory available for the purchased SKU size of the capacity. A single semantic model is still constrained to the memory limits of the SKU. Power BI uses dynamic memory management to evict inactive semantic models from memory. Semantic models are evicted so that Power BI can load other semantic models to address user queries.
Note
If you have to wait for an evicted semantic model to be reloaded, you might experience a noticeable delay.
On-demand load
On-demand load is enabled by default for large semantic models, and can provide significantly improved load time of evicted semantic models. With on-demand load, you get the following benefits during subsequent queries and refreshes:
Relevant data pages are loaded on-demand (paged in to memory).
Evicted semantic models are quickly made available for queries.
On-demand loading surfaces additional Dynamic Management View (DMV) information that can be used to identify usage patterns and understand the state of your models. For example, you can check the Temperature and Last Accessed statistics for each column in the semantic model, by running the following DMV query from SQL Server Management Studio (SSMS):
Select * from SYSTEMRESTRICTSCHEMA ($System.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS, [DATABASE_NAME] = '<Semantic model Name>')
Checking semantic model size
After loading historical data, you can use SSMS through the XMLA endpoint to check the estimated semantic model size in the model properties window.
You can also check the semantic model size by running the following DMV queries from SSMS. Sum the DICTIONARY_SIZE and USED_SIZE columns from the output to see the semantic model size in bytes.
SELECT * FROM SYSTEMRESTRICTSCHEMA
($System.DISCOVER_STORAGE_TABLE_COLUMNS,
[DATABASE_NAME] = '<Semantic model Name>') //Sum DICTIONARY_SIZE (bytes)
SELECT * FROM SYSTEMRESTRICTSCHEMA
($System.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS,
[DATABASE_NAME] = '<Semantic model Name>') //Sum USED_SIZE (bytes)
Default segment size
For semantic models using the large semantic model storage format, Power BI automatically sets the default segment size to 8 million rows to strike a good balance between memory requirements and query performance for large tables. This is the same segment size as in Azure Analysis Services. Keeping the segment sizes aligned helps ensure comparable performance characteristics when migrating a large data model from Azure Analysis Services to Power BI.
Considerations and limitations
Keep in mind the following restrictions when using large semantic models:
Supported regions: Large semantic models are available in Azure regions that support Azure Premium Files Storage. Review the table in region availability to see a list of all the supported regions.
Setting maximum semantic model size: Maximum semantic model size can be set by administrators. For more information, see Max Memory in Datasets.
Refreshing large semantic models: Semantic models that are close to half the size of the capacity size (for example, a 12-GB semantic model on a 25-GB capacity size) may exceed the available memory during refreshes. Using the enhanced refresh REST API or the XMLA endpoint, you can perform fine grained data refreshes, so that the memory needed by the refresh can be minimized to fit within your capacity's size.
Push semantic models: Push semantic models don't support the large semantic model storage format.
You can't use REST APIs to change the settings of a workspace to allow new semantic models to use the large semantic model storage format by default.
Region availability
Large semantic models in Power BI are only available in Azure regions that support Azure Premium Files Storage.
The following list provides regions where large semantic models in Power BI are available. Regions not in the following list aren't supported for large models.
Note
Once a large semantic model is created in a workspace, it must stay in that region. You can't reassign a workspace with a large semantic model to a Premium capacity in another region.
Azure region | Azure region abbreviation |
---|---|
Australia East | australiaeast |
Australia Southeast | australiasoutheast |
Austria East | austriaeast |
Brazil South | brazilsouth |
Brazil South B | brazilsouthb |
Canada Central | canadacentral |
Canada East | canadaeast |
Central India | centralindia |
Central US | centralus |
Chile Central | chilecentral |
East Asia | eastasia |
East US | eastus |
East US 2 | eastus2 |
France Central | francecentral |
France South | francesouth |
Germany North | germanynorth |
Germany West Central | germanywestcentral |
Indonesia Central | indonesiacentral |
Israel Central | israelcentral |
Italy North | Italynorth |
Japan East | japaneast |
Japan West | japanwest |
Korea Central | koreacentral |
Korea South | koreasouth |
Malaysia West | malaysiawest |
Mexico Central | mexicocentral |
New Zealand North | newzealandnorth |
North Central US | northcentralus |
North Europe | northeurope |
Norway East | norwayeast |
Norway West | norwaywest |
Poland Central | polandcentral |
Qatar Central | qatarcentral |
Singapore | singapore |
South Africa North | southafricanorth |
South Africa West | southafricawest |
South Central US | southcentralus |
Southeast Asia | southeastasia |
South India | southindia |
Spain Central | spaincentral |
Sweden Central | swedencentral |
Switzerland North | switzerlandnorth |
Switzerland West | switzerlandwest |
Taiwan North | taiwannorth |
Taiwan North West | taiwannorthwest |
UAE Central | uaecentral |
UAE North | uaenorth |
UK South | uksouth |
UK West | ukwest |
West Europe | westeurope |
West India | westindia |
West US | westus |
West US 2 | westus2 |
West US 3 | westus3 |
Related content
The following links provide information that can be useful for working with large models: