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A task was canceled
Starting 2 days ago, this error has been appearing when I refresh a dataflow that was previously working fine. As it is, the DF is a pretty simple one, soI tried removing quries and toggling the staging option because that's all I can do. But nothing helped. Anyone else experiencing some unexplainable error lately?
Solved! Go to Solution.
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I found a solution: add a filter rows step on some queries in the DF. Because this was previously not needed, I wonder if available backend resources has been reduced or unseen changes made to how datasets (>1 million rows) are processed.
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I found a solution: add a filter rows step on some queries in the DF. Because this was previously not needed, I wonder if available backend resources has been reduced or unseen changes made to how datasets (>1 million rows) are processed.
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Hi @ebjim
Glad that your query got resolved. Please continue using Fabric Community for any help regarding your queries.
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No gateway is in use. Additionally, I have 64 CUs and only one DF refreshing at any given time. I have also received another similar error:
999999 Couldn't refresh the entity because of an issue with the mashup document MashupException.Error: We're sorry, an error occurred during evaluation.
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Hi @ebjim
Thanks for the information. This error seems to be a bug or an undefined situation.
Apologies for the issue that you are facing.
This might require a deeper investigation from our engineering team about your workspace and the logic behind it to properly understand what might be happening.
Please go ahead and raise a support ticket to reach our support team:
https://support.fabric.microsoft.com/support
Please provide the ticket number here as we can keep an eye on it.
Thanks.
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Hi @ebjim
Thanks for using Fabric Community.
This might be an intermittent issue. Can you please try this after a day and let us know if the issue still persists?
You can also follow these troubleshooting steps:
- Check Gateway: If using a gateway, ensure it's online, up-to-date, and configured correctly for all data sources and destinations.
- Examine Capacity: If working in a shared capacity, confirm sufficient resources are available. Monitor capacity metrics for memory or CPU constraints.
Hope this helps. Please let me know if you have any further issues.

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