Forum Discussion
SQL Endpoint error: Failed to complete the command because the underlying location does not exist.
Sorry for the late response. I don't find a specific API or something else that can help refresh the SQL Endpoint of a lakehouse automatically. I captured the trace of the "refresh" action in Explorer. It seems trigger a metadata refresh of the SQL endpoint. But I failed to covert it into a valid call we can use for the automation process.
You may try setting a longer waiting time after starting the capacity. If this still doesn't work, I would suggest creating a support ticket to ask escalation engineers to help check the failue. This looks more like a synchronization issue.
In addition, a lakehouse generates a default semantic model. You can manage the default semantic model or create customized semantic models from it. Maybe you can consider using the default semantic model or customized semantic models for your reports. Default Power BI semantic models - Microsoft Fabric | Microsoft Learn
Best Regards,
Jing
Hi Anonymous
Let me explain better:
I created a Link to Fabric connection to get data from D365 CE (Dataverse).
After that, I created some views that read a few tables from the Lakehouse, and those views I connected them to a Power BI report (desktop to be specific) and then published my report.
Then I created a Logic App automation that starts the capacity in the morning, waits for around 20min, then refreshes the report.
Even after waiting 20min, I get the error of this case.
If I manually refresh the SQL Endpoint (by entering the SQL Endpoint and click on refresh button), I can refresh the report, but going this way I lose all the intention of automate the process..
Sorry for the late response. I don't find a specific API or something else that can help refresh the SQL Endpoint of a lakehouse automatically. I captured the trace of the "refresh" action in Explorer. It seems trigger a metadata refresh of the SQL endpoint. But I failed to covert it into a valid call we can use for the automation process.
You may try setting a longer waiting time after starting the capacity. If this still doesn't work, I would suggest creating a support ticket to ask escalation engineers to help check the failue. This looks more like a synchronization issue.
In addition, a lakehouse generates a default semantic model. You can manage the default semantic model or create customized semantic models from it. Maybe you can consider using the default semantic model or customized semantic models for your reports. Default Power BI semantic models - Microsoft Fabric | Microsoft Learn
Best Regards,
Jing
Hi Anonymous
I tested waiting for 45min and seems o be working. It's not the best scenario but at least we're not facing any issues.
Here is also a suggested way to check if the SQL Analytics Endpoint has synced:
I like the idea of the canary table - easy enough to include in the ETL process and then easy enough to drop - unless that also has a delay?
