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Arpan
New Member

DataSet scheduled and manual refresh fails with error Command has been canceled

I am continuously getting the below error when I try to refresh the dataset. The dataset refresh fails on manual as well as scheduled refresh. I am able to refresh the data just fine in the power bi project that I published. Can someone please help? Doesnt look like dataset size, timeout or bandwidth issue as the DataSet refresh fails within 10 secs. My dataset pulls data from - Kusto and analytics.dev.azure.com. It has 5 tables.

 

Something went wrong
There was an error when processing the data in the dataset.
Please try again later or contact support. If you contact support, please provide these details.
Message: The command has been canceled. Table: TABLENAME.
Cluster URI: DF-MSIT-SCUS-redirect.analysis.windows.net
Activity ID: af4cf800-75e0-4555-a67b-61917bb5ceae
Request ID: ab13c0ae-70df-545e-824b-fa429dca4d97
Time: 2019-04-24 23:43:32Z

 

2 REPLIES 2
v-frfei-msft
Community Support
Community Support

Hi @Arpan ,

 

As this case, the issue is related to high density of data and low network bandwidth. So please check your net work and shut down others processes to try again.

 

Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.

Hi @v-frfei-msft 

 

The report is being refreshed from a msft network so i dont think bandwidth is the issue here. Also i am not sure what you mean by high density of data. Can you please elaborate and provide any suggestions on how to resolve this?

 

I tried removing all tables one by one and eventually I started getting "internal service error" on the last table. I need help from Power BI support to debug this.

 

This is the error i received:

 

Something went wrong
The last refresh attempt failed because of an internal service error.
Please try again later or contact support. If you contact support, please provide these details.
Cluster URI: DF-MSIT-SCUS-redirect.analysis.windows.net
Activity ID: af4cf800-75e0-4555-a67b-61917bb5ceae
Request ID: c862949e-2fd8-0057-9e3d-ad8e7720da2b
Time: 2019-04-26 06:22:30Z

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