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Timeseries tags

  • 12 July 2023
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I have a lot of timeseries objects in CDF datasets. I have a particular set of timeseries tags out of the innumerable list of timeseries objects (16 of them) and for each tag, there are a bunch of sub-tags (4 of them). So, in total, I will need to maintain a hierarchy of 16 tags and each having 4 tags and the overall total of 64 tags. I need to go and retrieve the datapoints for each of those 64 tags. So how do I store my desired list of timeseries tags along with their child tags within CDF. Where do I store them and maintain them. This list may be edited and needs flexibility to be edited based on business users need. IT is completely the enterprise choice.  Please share complete steps simulate them in CDF. 

This is actually to be done for yield-tracking analytics and all these tags corresponding to the yield groups/products in a refinery.

 

 

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Best answer by roman.chesnokov 12 July 2023, 12:15

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Hey @eashwar11 , it seems that you just need to create an asset hierarchy using SDK or CDF Transformations and assign your time-series to the assets. Then you can use Python SDK method .subtree() to retrieve all the time-series from hierarchy or assets.retrieve() to get a particular asset (tag). Please inform me if you have any further inquiries.

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Thanks @roman.chesnokov  for the inputs. But is it okay to store the timeseries tags as ‘assets’?

Will that be good? I thought only asset information is only to be maintained as ‘Assets’.

Here, I have around 343k timeseries objects in total, but I wanted to maintain a list of 18 parent tags and each of those having 4 tags attached to the parent. 

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@eashwar11 So as far as I understand you have a lot of time-series and you want to use only a few of them in a hierarchical structure?  That’s the perfect setup for using ‘Assets’ as I see that. You need to create a few additional objects, an asset per tag, but it will allow you to represent the hierarchical structure perfectly. You can also use Data Modeling capabilities, but it will probably be overkill for that task.

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