Forum Discussion
Issue with Session Start After Switching to Schema-Enabled Lakehouse
Hello everyone,
I recently created a notebook in Fabric and developed everything using Python. Initially, I had a Lakehouse attached, but after switching to a schema-enabled Lakehouse (using the Preview feature), I started encountering errors when trying to start a session.
Error Details
When executing a cell, I get the following error:
Additional Diagnostic Information
- The session fails with a message indicating:{
"type": "close",
"timeStamp": 451766,
"code": 1000,
"reason": "{\"reason\":\"Session error or stopped.\",\"state\":\"session-completed\"}",
"wasClean": false,
"target": { - The issue persists even after restarting the notebook and deleting browser data.
Has anyone else encountered this after enabling schemas in Lakehouse? Any insights or potential workarounds would be greatly appreciated!
Thanks in advance.
Hello PhilippMer
The error message you received highlights one of the primary limitations of the schema-enabled Lakehouse feature: workspace naming restrictions. Microsoft specifically requires that workspace names must only contain alphanumeric characters when using schema-enabled Lakehouses.
Coukd you please check the workspace name once again.
3 Replies
- nilendraFabric
Super User
Hello PhilippMer
The error message you received highlights one of the primary limitations of the schema-enabled Lakehouse feature: workspace naming restrictions. Microsoft specifically requires that workspace names must only contain alphanumeric characters when using schema-enabled Lakehouses.
Coukd you please check the workspace name once again.Thank you very much, you are absolutely right. The error message did not indicate that sadly, but it solved my error.
v-karpurapudCommunity Support
Hello PhilippMer
Could you please confirm if your query have been resolved the solution provided by nilendraFabric ? If they have, kindly mark the helpful response and accept it as the solution. This will assist other community members in resolving similar issues more efficiently.
Thank you
