Forum Discussion
Getting error when we try to Connect to the Power BI Semantic model created in the Fabric Lakehouse
Thanks for sharing the details. We are using Small Semantic model storage format and Fabric capacity. Please let us know the limitations for this Fabric Capacity with CU of F512 units. in terms of number of Lakehouses and Semantic Models and artifacts can be created. Please let us know the limitations or size of the semantic model supported for Small Semantic model storage format and any other limitations which is causing the performance issues.
I think the Fallback link has some information about the limits:
Ref. also Semantic model SKU limitation
What is the size (number of rows) of the lakehouse tables you are attempting to query in Direct Lake mode?
And how many columns from the lakehouse table are involved in your queries (=visuals)?
This blog post explains about paging and memory consumption when using Direct Lake.
I am not sure if the "Small Semantic model storage format" or "Large Semantic model storage format" matters for Direct Lake semantic models.
I think maybe it just matters if you store the data within the semantic model (e.g. Import mode semantic model).
Ref. Solved: Storage format for workspace with Fabric direct la... - Microsoft Fabric Community
However this thread could potentially imply that the "Small Semantic model storage format" may have an effect also on Direct Lake queries: Solved: Change semantic model size from small to large - Microsoft Fabric Community
I must admit I am unsure about the role of Small vs. Large semantic model storage format when it comes to Direct Lake. Hope someone can clarify.