Cognite Data Fusion: Move Magic Datapoint Granularity Selection Algorithm From Direct Query to the API

Related products: API and SDKs

I have been playing around with the excellent DirectQuery preview functionality and really enjoyed that I can simply give it a timestamp range and it figures out how many points I need and what the granularity will be with the assumption that I will use the queried data for some visualization.  Even if someone has an 8K monitor with no border around their chart, with one pixel per point the most I could possibly need would be 7680 datapoints.  Reality is that we need much less since we show a datapoint as more than a pixel width.  But I don’t have to care about that complexity.  Cognite calculates optimal granularity for me.

 

Can this feature also be available via the API for “Retrieve data points”?
https://docs.cognite.com/api/v1/#tag/Time-series/operation/getMultiTimeSeriesDatapoints

Maybe we would be able to set granularity to “auto” then the magic happens?

 

Once the magic is implemented in the API then the implementation in DirectQuery gets simplified, right?


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