Most efficient query method when source is URL with static date range

[kahuna965]

Hello,  I have several configuarble URL's for which I can attain data in csv format.   In attempt to limit the query time, I was curious as to what the best strategy would be for configuring the connection and URL alike.  My url string is as follows:   http://192.168.1.1:8000/timestamped/listByPatternToCSV?prefix=MC&from=2022-08-12&to=2023-01-01.  Should I parameterize the date ranges and then bind them to tables for date selection that the user can configure?  I found an example of this method here https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-dynamic-m-query-parameters. 

Alternately, would using incremental refresh with an open ended "end date" be a better approach?   

Appreciate the groups thoughts!

[Anonymous]

Hi @kahuna965 ,

I'm a little confused about your needs, Could you please explain them further?

Thanks for your efforts & time in advance.

Best regards,
Community Support Team_ Binbin Yu

[kahuna965 · Accepted solution]

Hello,

I may have answered my own question with some additional research.  Because my only source for data is url based, my primary concern was that the query would take too much time.  The data imported has close to 100 columns and several thousand rows.   I didn't want to stress whatever service was creating the data, hence the path i took was to make paramters.  For the two date fields in the url i shared, my intent was to bind those to paramters in my report thus allowing the date range to be modified in the URL.  Turns out that only works with direct query.  

It seems the only way i can make this work is to periodically adjust paramters so the url is not trying to return too much data.