Don't miss your chance to take the Fabric Data Engineer (DP-700) exam on us!
Learn moreThe FabCon + SQLCon recap series starts April 14th at 8am Pacific. If you’re tracking where AI is going inside Fabric, this first session is a can't miss. Register now
Hi,
In power bi service is there any any setting that control the time of exection of semantic model refresh?
If the model taking long running, we need to set the default time to aborted.
can anyone tell where the setting are in serivce/
Thanks,
Sri.
Solved! Go to Solution.
Hii @Koritala
The timeout limits are predefined by the service: Shared capacity (Pro) refresh can run up to 2 hours, while Premium capacity allows up to 5 hours per refresh. If a refresh exceeds these limits, it is automatically aborted. There is no configurable setting in the Power BI Service UI to modify this timeout; optimization of the dataset or use of Premium capacity is the typical approach if refresh duration is an issue.
You could achieve this by using Pipelines for refreshing your semantic models. If the process time exceeds timeout limit the refresh activity would be failed
Hi @Koritala ,
Thanks for reaching out to the Microsoft fabric community forum.
Power BI Service does not offer a configurable setting for execution timeout during semantic model refreshes. The platform manages refresh duration limits, which cannot be adjusted via dataset, workspace, or gateway settings. In shared capacity, refreshes may run for up to two hours, while Premium capacity and Premium Per User workspaces allow up to five hours. If these limits are exceeded, the service will automatically terminate the refresh process.
To address refresh duration issues, it is recommended to optimize the semantic model or Power Query transformations, or to implement incremental refresh to process only recent data. For larger datasets or extended processing needs, Premium capacity provides a longer refresh window and additional resources.
Thank you.
Hi @Koritala ,
Thanks for reaching out to the Microsoft fabric community forum.
Power BI Service does not offer a configurable setting for execution timeout during semantic model refreshes. The platform manages refresh duration limits, which cannot be adjusted via dataset, workspace, or gateway settings. In shared capacity, refreshes may run for up to two hours, while Premium capacity and Premium Per User workspaces allow up to five hours. If these limits are exceeded, the service will automatically terminate the refresh process.
To address refresh duration issues, it is recommended to optimize the semantic model or Power Query transformations, or to implement incremental refresh to process only recent data. For larger datasets or extended processing needs, Premium capacity provides a longer refresh window and additional resources.
Thank you.
Hi @Koritala ,
I wanted to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions.
Thank you.
Hi @Koritala ,
I wanted to follow up and see if you had a chance to review the information shared. If you have any further questions or need additional assistance, feel free to reach out.
Thank you.
You could achieve this by using Pipelines for refreshing your semantic models. If the process time exceeds timeout limit the refresh activity would be failed
Hii @Koritala
The timeout limits are predefined by the service: Shared capacity (Pro) refresh can run up to 2 hours, while Premium capacity allows up to 5 hours per refresh. If a refresh exceeds these limits, it is automatically aborted. There is no configurable setting in the Power BI Service UI to modify this timeout; optimization of the dataset or use of Premium capacity is the typical approach if refresh duration is an issue.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 29 | |
| 23 | |
| 17 | |
| 16 | |
| 14 |