Forum Discussion
Visuals exceeded power bi resources
My report has 3 million rows per date, and there is data for two dates, I put a filter for one date and I get
visuals exceed power bi resources error
I am using Drect Query, does this error occur only for direct query ? if I change it to import will it help ? I was not getting this error before. I use P1 SKU
Also, how can i measure the size of my dataset in power bi ? I have premium capacity so the CapacityMetrics app will tell me that?
Also, if I leave some of the numeric columns as default sum will it hlep ?
6 Replies
- GilbertQSuper User
Hi Anonymous
This is because I think a visual has a limitation of how many rows can be returned. When you then combine this with DirectQuery it exceeds the values.
I would suggest importing and then using a measure to achieve the same result
here are more details: Large datasets, data point limits, and data strategies - Power BI | Microsoft Docs
- AnonymousNot applicable
The visual limitation for number of rows limits apply in import mode too ?
- GilbertQSuper User
Hi Anonymous
It should apply, but if you are using a measure it should not return each individual row but rather a single row by date.
- v-cazheng-msftCommunity Support
Hi Anonymous
For Direct Query, the number of rows returned by single query cannot exceed 1 million rows. If the calculation is too complicated or the amount of data to be queried is large, the query time will be relatively long and it possibly fail. If you change the connection mode from Direct Query to Import, what you need to pay attention to is the limitation on the size of the uploaded dataset. For P1 capacity, the publish limitation is less than 3 GB. Normally, the file size is close to the size of the dataset, you can judge the size of the dataset by the file size.
When the amount of data is very large, we strongly recommend that you do some aggregation calculations in the data source in advance, delete unnecessary data and simplify the calculations in the model and the relationships between tables. This can not only shorten the response time of the interaction, but also speed up the refresh of the dataset.
Best Regards
Caiyun Zheng
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