Forum Discussion
Failed to complete the command because the underlying location does not exist LakehouseSQL Endpoint
Our data hasn't been udpated in a week and this query that we have been running has been running successfully for a week until today. We got
SELECT * FROM table WHERE 1=1 AND id = <id>
AND date >= '[3 years from now]' ORDER BY updated_date
"internalMessage" : "('42000', \"[42000] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Failed to complete the command because the underlying location does not exist. Underlying data description: table <table> (24596) (SQLExecDirectW)\")"
Has anyone encountered this and know how to fix this?
Hello Anonymous
The SQL Endpoint’s metadata (table/file references) becomes temporarily out of sync with the actual Delta tables in the Lakehouse. This causes queries to reference outdated file paths (e.g., GUID-based Parquet files that no longer exist). The error code `24596` explicitly indicates this mismatch
This issue was discussed many times in the forum. Although it is never mentioned in known issues in Fabric docs
try Manually trigger a metadata refresh on the Lakehouse via Fabric’s UI to force the SQL Endpoint to sync
Right-click Lakehouse → Refresh
Modify your pipeline to include a retry loop with a 30–60-second wait between attempts
workarounds like forced refreshes and retries often resolve it. For critical systems, consider using Delta Lake directly
if this is helpful please accept the answer
8 Replies
Hello Anonymous
The SQL Endpoint’s metadata (table/file references) becomes temporarily out of sync with the actual Delta tables in the Lakehouse. This causes queries to reference outdated file paths (e.g., GUID-based Parquet files that no longer exist). The error code `24596` explicitly indicates this mismatch
This issue was discussed many times in the forum. Although it is never mentioned in known issues in Fabric docs
try Manually trigger a metadata refresh on the Lakehouse via Fabric’s UI to force the SQL Endpoint to sync
Right-click Lakehouse → Refresh
Modify your pipeline to include a retry loop with a 30–60-second wait between attempts
workarounds like forced refreshes and retries often resolve it. For critical systems, consider using Delta Lake directly
if this is helpful please accept the answer
Anonymous did you manage to solve this issue?
I also tried the refresh buttons but it did not fix it
nilendraFabric any ideas?
`%%sql` bypasses the SQL Endpoint and runs SparkSQL directly against the Lakehouse’s Delta tables
Spark reads Delta transaction logs directly from `/tables`, avoiding SQL Endpoint sync delaysFor now if you want to use sql. Go with this approach.
if this issue persists raise a support ticket
Anonymous, As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for your issue worked? or let us know if you need any further assistance here?
nilendraFabric, Thanks for your promt response.
Thanks,
Prashanth Are
MS Fabric community support
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly and give Kudos if helped you resolve your query
Anonymous, As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for your issue worked? or let us know if you need any further assistance here?
Thanks,
Prashanth Are
MS Fabric community support
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly and give Kudos if helped you resolve your query
Anonymous As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for your issue worked? or let us know if you need any further assistance here?
if issue still persists i suggest you to raise a support ticket here. so, that they can assit you in addressing the issue you are facing. please follow below link on how to raise a support ticket:
How to create a Fabric and Power BI Support ticket - Power BI | Microsoft Learn
Thanks,
Prashanth Are
MS Fabric community support
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly and give Kudos if helped you resolve your query
