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Workener
Frequent Visitor

OData Performance: Querying the whole feed and filtering it with ui vs querying a filtered feed

Hello,

 

I'm relatively new to PowerBI, so this should be an easy question for you. If I build reports e.g. In Excel I try to get as less data back as possible (using select and filter statement) when I use OData to achieve an adequate performance.

 

How is the best practice in PowerBI? Is the performance the same as in the example above, if I query the whole feed and filter it down afterwards with the ui (select tables, use the query editor in order to delete columns)?

 

A feedback would be highly appreciated. Thank you!

 

Best regards,

workener

1 ACCEPTED SOLUTION
v-ljerr-msft
Microsoft Employee
Microsoft Employee

Hi @Workener,

Currently when you specify filters (Table.SelectRows) on navigation property the predicate does not get pushed to the URL. PowerBI Desktop downloads all the data locally and then does filtering client-side. This is very inefficient. It would be great if OData.Feed was smart enough to push predicates on navigation properties to URLs.

In this scenario, I would suggest you query a filtered feed instead of querying the whole feed and filtering it with ur(the same as using Table.SelectRows M function) currently. Here is the idea shared on Power BI Ideas for your reference. Smiley Happy

 

Regards

View solution in original post

1 REPLY 1
v-ljerr-msft
Microsoft Employee
Microsoft Employee

Hi @Workener,

Currently when you specify filters (Table.SelectRows) on navigation property the predicate does not get pushed to the URL. PowerBI Desktop downloads all the data locally and then does filtering client-side. This is very inefficient. It would be great if OData.Feed was smart enough to push predicates on navigation properties to URLs.

In this scenario, I would suggest you query a filtered feed instead of querying the whole feed and filtering it with ur(the same as using Table.SelectRows M function) currently. Here is the idea shared on Power BI Ideas for your reference. Smiley Happy

 

Regards

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