Forum Discussion
Table UPDATE statements on the same Warehouse table.
I am using Microsoft Fabric Data Pipelines with a ForEach activity to run multiple UPDATE statements on the same Warehouse table.
When multiple updates run at the same time, I get concurrency or locking errors.
I tried reducing the batch count in the ForEach activity, but the issue still occurs when updates run in parallel.
My questions are:
Is there a way to avoid locking or conflicts when running parallel updates on the same table?
Would partitioning the table (for example by ID) help prevent these conflicts?
What is the recommended design pattern in Fabric for handling this scenario?
Currently, each iteration updates the table like:
UPDATE my_table
SET column = value
WHERE id = Item()
Any guidance or best practices would be appreciated.
Hi Abdul_Ismail,
Thank you tayloramy, for your insights.
This issue happens because parallel UPDATE statements on the same table create write-write conflicts under snapshot isolation in Microsoft Fabric. To fix this, avoid updating rows in parallel and use a set-based method like staging with MERGE or batch updates to minimize concurrent transactions. If necessary, run the ForEach activity sequentially (batch count = 1) and include retry logic to manage transient conflicts.
Transactions in Fabric Data Warehouse - Microsoft Fabric | Microsoft Learn
Troubleshoot the Warehouse - Microsoft Fabric | Microsoft Learn
Thank you.
4 Replies
Hi Abdul_Ismail,
Fabric warehouses use Intent Exclusive (IX) locks for update statements, so there is no nice way to run multiple updates on the same table at the same time.
My recommendation would be to use a staging pattern, stage all your new records in a staging table, and then run a merge statement to update the final warehouse table all in one go.
Hi Abdul_Ismail,
Thank you tayloramy, for your insights.
This issue happens because parallel UPDATE statements on the same table create write-write conflicts under snapshot isolation in Microsoft Fabric. To fix this, avoid updating rows in parallel and use a set-based method like staging with MERGE or batch updates to minimize concurrent transactions. If necessary, run the ForEach activity sequentially (batch count = 1) and include retry logic to manage transient conflicts.
Transactions in Fabric Data Warehouse - Microsoft Fabric | Microsoft Learn
Troubleshoot the Warehouse - Microsoft Fabric | Microsoft Learn
Thank you.
HI Abdul_Ismail,
Have you had a chance to review the solution we shared earlier? If the issue persists, feel free to reply so we can help further.
Thank you.
HI Abdul_Ismail,
Checking in to see if your issue has been resolved. let us know if you still need any assistance.
Thank you.
