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azadthakur
Frequent Visitor

Time out issue 225 sec

Hello Power BI Team,

I am currently working on a semantic model dataset that is approximately 3.5 GB in size. Users are generating reports using this dataset with direct query mode. However, they are encountering difficulties interpreting some results in the matrix visual and experiencing time-out errors, such as "The XML for Analysis request timed out before it was completed. Timeout value: 225 sec."

In my efforts to resolve this issue, I discovered that we need to adjust the query limit settings in Power BI Desktop under the report settings for the current file. Could you please provide guidance on the optimal settings for a dataset of this size? Additionally, I would like to know if these settings should be applied to the user report, the dataset, or both.

I have attached a snapshot of the current settings for your reference. Your assistance in this matter would be greatly appreciated.

Best regards,

Azad

PBI setting.png

2 ACCEPTED SOLUTIONS
lbendlin
Super User
Super User

Before you do that, consider the impact on the report users.  Do you really want to let them wait 225 seconds for the visual to render?   Maybe spend your resources evaluating the queries and refactoring them to run faster and/or to improve the data model.

View solution in original post

Anonymous
Not applicable

Hi, @azadthakur 

Thanks for @lbendlin reply. Here are some additions.

The max refresh time setting in the image you gave works in the service.
vyaningymsft_0-1719283457907.png

You can also specify it in Power Query, referring to the reply in the link below.
vyaningymsft_1-1719284248684.png
How to extend Power BI service timeout limit - Page 2 - Microsoft Fabric Community

If your customers have requirements for refresh times, consider optimizing your data model to use incremental refresh whenever possible, using incremental refresh (if supported), creating appropriate indexes, maintaining statistics, and optimizing query performance. If possible, break up large datasets into smaller subsets and refresh them separately in the Power BI service.

 

Troubleshooting automatic aggregations to optimize DirectQuery performance | Microsoft Power BI Blog...

Best Regards,
Yang

Community Support Team

 

If there is any post helps, then please consider Accept it as the solution to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Thanks a lot!

How to get your questions answered quickly --  How to provide sample data in the Power BI Forum

View solution in original post

2 REPLIES 2
Anonymous
Not applicable

Hi, @azadthakur 

Thanks for @lbendlin reply. Here are some additions.

The max refresh time setting in the image you gave works in the service.
vyaningymsft_0-1719283457907.png

You can also specify it in Power Query, referring to the reply in the link below.
vyaningymsft_1-1719284248684.png
How to extend Power BI service timeout limit - Page 2 - Microsoft Fabric Community

If your customers have requirements for refresh times, consider optimizing your data model to use incremental refresh whenever possible, using incremental refresh (if supported), creating appropriate indexes, maintaining statistics, and optimizing query performance. If possible, break up large datasets into smaller subsets and refresh them separately in the Power BI service.

 

Troubleshooting automatic aggregations to optimize DirectQuery performance | Microsoft Power BI Blog...

Best Regards,
Yang

Community Support Team

 

If there is any post helps, then please consider Accept it as the solution to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Thanks a lot!

How to get your questions answered quickly --  How to provide sample data in the Power BI Forum

lbendlin
Super User
Super User

Before you do that, consider the impact on the report users.  Do you really want to let them wait 225 seconds for the visual to render?   Maybe spend your resources evaluating the queries and refactoring them to run faster and/or to improve the data model.

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