topic Re: Error Data Warehouse/Lakehouse in Data Engineering

Error Data Warehouse/Lakehouse

HarderT — Mon, 26 May 2025 09:12:55 GMT

Hey together,

since last week our Data Warehouse connection had errors:

"Message=<ccon>Warning: Fatal error 615 occurred at May 26 2025 8:08AM. Note the error and time, and contact your system administrator.\r\nLogin failed for user '<token-identified principal>'.</ccon>, Code=21, State=1"

AND

ErrorCode=SqlFailedToConnect,'Type=Microsoft.DataTransfer.Common.Shared.HybridDeliveryException,Message=Cannot connect to SQL Database. Please contact SQL server team for further support. Server: 'xxx', Database: 'xxx', User: ''. Check the connection configuration is correct, and make sure the SQL Database firewall allows the Data Factory runtime to access.,Source=Microsoft.DataTransfer.Connectors.MSSQL,''Type=Microsoft.Data.SqlClient.SqlException,Message=Warning: Fatal error 615 occurred at May 22 2025 12:15AM. Note the error and time, and contact your system administrator.
Login failed for user '<token-identified principal>'.,Source=Framework Microsoft SqlClient Data Provider,'

I have restored the database, but the lakehouses have the same errors. When I look at the tables in the Lakehouse view, I see data but when I switch to the SQL endpoint, I no longer see any data and the error message appears. This is all since May 22nd, since the MS Fabric update.

Is there a Solution for the Lakehouse

Many thanks

Re: Error Data Warehouse/Lakehouse

Anonymous — Mon, 26 May 2025 12:10:15 GMT

Hi HarderT,

Thank you for reaching out to Microsoft Fabric Community Forum.

At this time, there is no option in Fabric to disable or re-enable the SQL endpoint manually, and the issue requires backend support from Microsoft to resolve.

As a temporary workaround, copy your tables to a new Lakehouse using a Spark notebook, which will reinitialize the SQL endpoint properly.

Since error 615 is a fatal metadata/page-level error and the SQL endpoint is broken even though data is visible in Lakehouse Explorer, it likely needs backend repair by the Microsoft Fabric team.

Please raise a support ticket with Microsoft, referencing the exact error message and timestamp.
https://learn.microsoft.com/en-us/power-bi/support/create-support-ticket

If this post helps, then please consider Accepting as solution to help the other members find it more quickly, don't forget to give a "Kudos" – I’d truly appreciate it!

Regards,
Vinay Pabbu

Re: Error Data Warehouse/Lakehouse

HarderT — Mon, 26 May 2025 14:48:07 GMT

Anonymous thanks for your quick respond. But I need a quicker solution.

Is there any way, where I can rebind a semantic model from one lakehouse to an other?

Because I want to save myself the work of recreating everything. That's why I want to create a new lakehouse and connect the source data there and then convert the semantic model on which reports are already based to it

Re: Error Data Warehouse/Lakehouse

Anonymous — Tue, 27 May 2025 09:35:02 GMT

Hi HarderT,

Yes, you can rebind the semantic model to a new Lakehouse. Just make sure the new Lakehouse has the same table names and structure. Then open the semantic model in Power BI Desktop, go to Data source settings, and point it to the new Lakehouse’s SQL endpoint. After that, publish it back.

Regards,

Vinay Pabbu

Re: Error Data Warehouse/Lakehouse

Anonymous — Thu, 29 May 2025 13:11:42 GMT

Hi HarderT,

As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for the issue worked? or Let us know if you need any further assistance?
If our response addressed, please mark it as Accept as solution and click Yes if you found it helpful.

Regards,
Vinay Pabbu

Re: Error Data Warehouse/Lakehouse

HarderT — Mon, 02 Jun 2025 08:50:05 GMT

Hi Anonymous,

the Problem now is when we change the connection it creates a new report and does not overwrite the old one.

Re: Error Data Warehouse/Lakehouse

Anonymous — Mon, 02 Jun 2025 10:50:23 GMT

Hi HarderT,

Thats the Default behaviour. Power BI treats it as a new data source, which results in a new report being created instead of overwriting the existing one.
if you're using Power BI Desktop, you can try updating the connection string from within the file and republish it, which should overwrite the existing report.

Regards,

Vinay Pabbu

Re: Error Data Warehouse/Lakehouse

Anonymous — Thu, 05 Jun 2025 10:14:49 GMT

Hi @HarderT,

Regards,
Vinay Pabbu

Re: Error Data Warehouse/Lakehouse

Anonymous — Mon, 09 Jun 2025 11:40:46 GMT

Hi HarderT,

As we haven't heard back from you, I hope you have raised a support ticket. At this time we are closing this thread. If you have any further issues, please start a new thread in the community forum, and we are here to assist you. Thankyou for your understanding and continuous support.
Thank you for being part of the Microsoft Fabric Community.

Regards,

Vinay Pabbu

Re: Error Data Warehouse/Lakehouse

Srisakthi — Tue, 10 Jun 2025 09:50:44 GMT

Hi HarderT ,

You can utilise Semantic Link Labs to repoint to new lakehouse.

import sempy.fabric as fabric

from sempy_labs.directlake._get_shared_expression import get_shared_expression

from sempy_labs._helper_functions import (

resolve_lakehouse_name,

)

from sempy_labs.tom import connect_semantic_model

from typing import Optional

import sempy_labs._icons as icons

def update_direct_lake_model_lakehouse_connection(

dataset: str,

workspace: Optional[str] = None,

lakehouse: Optional[str] = None,

lakehouse_workspace: Optional[str] = None,

😞

"""

Remaps a Direct Lake semantic model's SQL Endpoint connection to a new lakehouse.

Parameters

----------

dataset : str

Name of the semantic model.

workspace : str, default=None

The Fabric workspace name in which the semantic model exists.

Defaults to None which resolves to the workspace of the attached lakehouse

or if no lakehouse attached, resolves to the workspace of the notebook.

lakehouse : str, default=None

The Fabric lakehouse used by the Direct Lake semantic model.

Defaults to None which resolves to the lakehouse attached to the notebook.

lakehouse_workspace : str, default=None

The Fabric workspace used by the lakehouse.

Defaults to None which resolves to the workspace of the attached lakehouse

or if no lakehouse attached, resolves to the workspace of the notebook.

Returns

-------

"""

workspace = fabric.resolve_workspace_name(workspace)

if lakehouse_workspace is None:

lakehouse_workspace = workspace

if lakehouse is None:

lakehouse_id = fabric.get_lakehouse_id()

lakehouse = resolve_lakehouse_name(lakehouse_id, lakehouse_workspace)

# Check if lakehouse is valid

dfI = fabric.list_items(workspace=lakehouse_workspace, type="Lakehouse")

dfI_filt = dfI[(dfI["Display Name"] == lakehouse)]

if len(dfI_filt) == 0:

raise ValueError(

f"{icons.red_dot} The '{lakehouse}' lakehouse does not exist within the '{lakehouse_workspace}' workspace. "

f"Therefore it cannot be used to support the '{dataset}' semantic model within the '{workspace}' workspace."

)

dfP = fabric.list_partitions(dataset=dataset, workspace=workspace)

dfP_filt = dfP[dfP["Mode"] == "DirectLake"]

if len(dfP_filt) == 0:

raise ValueError(

f"{icons.red_dot} The '{dataset}' semantic model is not in Direct Lake. This function is only applicable to Direct Lake semantic models."

)

else:

with connect_semantic_model(

dataset=dataset, readonly=False, workspace=workspace

) as tom:

shEx = get_shared_expression(lakehouse, lakehouse_workspace)

try:

tom.model.Expressions["DatabaseQuery"].Expression = shEx

print(

f"{icons.green_dot} The expression in the '{dataset}' semantic model has been updated to point to the '{lakehouse}' lakehouse in the '{lakehouse_workspace}' workspace."

)

except Exception as e:

raise ValueError(

f"{icons.red_dot} The expression in the '{dataset}' semantic model was not updated."

) from e

Try the above code. Simalarly you can repoint the reports

Reference: https://github.com/microsoft/semantic-link-labs/blob/main/src/sempy_labs/directlake/_update_directlake_model_lakehouse_connection.py

Regards,

Srisakthi

If this helps, please mark is Accept As Solution