Forum Discussion
Post PatronPower BI Semantic Model Size Limit With PPU License
Hi All,
I have a PPU p3 license, with this can I build an individual semantic model in a desktop that has a size of more than 10 GB?
Regards,
Sri
if you've already implemented all the best practices to make this model as thin as possible and you're above 10 GB aswell, the suggested approach is to add parameters in Power Query to import just a portion of your data (years subset could be a good filtering) and then publish to the service modifying the paramters to include the whole dataset needed.
(optional) if you use datetime parameters you can think to setup an incremental refresh (remember to check if redshift is a foldable source).
remember to set it as Large Semantic Model and read carefully all the limitations of that setup.
7 Replies
R1k91Super User
It doesn't matter which license you have in PBI desktop.
You can create a model bigget than 10GB, the problem is when you publish to the cloud.
To go above 10GB you need to enable "Large Semantic Model"
Large semantic models in Power BI Premium - Microsoft Fabric | Microsoft Learn
PPU supports up to 100GB per model but beaware that 100GB is the maximum amount of memory available for your model that means it must enough for refresh and for users' query.
Power BI Premium Per User - Microsoft Fabric | Microsoft Learn
KoritalaHi Riccardo Perico,
Sorry, for the late response.
One thing I want to let you know is, as we have a large tables in redshift database and when we tried to connect in import mode, I am getting the memory issue in desktop before publishing to service itself.
How can we overcome in this. As you are saying, in desktop version, there is no limit with respect to single .pbxi sematic model.
Please let me know if my understanding is not correct.
Regards,
Srinivas.
- R1k91
if you've already implemented all the best practices to make this model as thin as possible and you're above 10 GB aswell, the suggested approach is to add parameters in Power Query to import just a portion of your data (years subset could be a good filtering) and then publish to the service modifying the paramters to include the whole dataset needed.
(optional) if you use datetime parameters you can think to setup an incremental refresh (remember to check if redshift is a foldable source).
remember to set it as Large Semantic Model and read carefully all the limitations of that setup.
v-hashadapuCommunity Support
Hi Koritala , Hope you're doing okay! May we know if it worked for you, or are you still experiencing difficulties? Let us know — your feedback can really help others in the same situation.
- v-hashadapu
Hi Koritala , Thank you for reaching out to the Microsoft Community Forum.
As R1k91 said, PPU with Large Semantic Model supports up to 100 GB per dataset in the service and that the service limits are different from Desktop. Parameterizing your query to load only a subset locally, then expanding it in the service, is a valid workaround and that incremental refresh can help if your source supports folding.
Power BI Desktop is bound by your local machine’s RAM and CPU. VertiPaq needs significantly more memory during processing than the final compressed model size, so large imports from Redshift can fail locally even if they would fit in the service. You can’t bypass that hardware limit, the fix is to avoid importing the full dataset in Desktop. Build on a filtered subset with parameters, publish, then expand in the service where your PPU capacity applies. If you need full data access without local import, consider DirectQuery, hybrid tables or staging data in a service-hosted dataflow.
Thank you R1k91 for your continued support in the community.
- v-hashadapu
Hi Koritala , Hope you are doing well. Kindly let us know if the issue has been resolved or if further assistance is needed. Your input could be helpful to others in the community.
- v-hashadapu
Hi Koritala , Hope you're doing fine. Can you confirm if the problem is solved or still persists? Sharing your details will help others in the community.