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Hi everyone, 

I tried to upload my own dataset(time-series data) into CDF, but I always get error: Request with id 87b235ea-78dd-963a-b343-ff58a0ee084d to https://westeurope-1.cognitedata.com/api/v1/projects/learn/timeseries/data failed with status 400: Timestamp is too high, must be at most 2556143999999 which is 31-12-2050 23:59:59 GMT.

I followed with this link:https://learn.cognite.com/path/cognite-data-fusion-fundamentals/working-with-cdf-integrate. I created an assest, 3 time-series. What I want to do is to upload my data to the 3 time-series, and show the variation of my data in CDF. I change the time_stamp of my data into the format of 2022-02-10T17:00:00.000Z, I am not sure if this is necessary but when I preview my datapoints in RAW explorer and CDF automatically change the this format into for example, 164998440000, so I am wondering if this is why I have this error? I also want to ask what is the meaning of span in IFSDB.sensors? It means this time-series is 100 days? or 100 hours? Not sure if this will be related to my error.

You can always find my project in cognite-learn.fusion.cognite.com. My Data sets is called ‘Lab’, you can also preview my data set in RAW explorer, also search for ‘Lab’, and there are 5 csv files, my datapoints value is in ‘Values1’. If you want to see how I transform my data, please refer to ‘Yiming1999-solarTimes’, ‘Yiming1999-solarDataPoints’,’Yiming1999-solarEvents’,’Yiming1999-soalrAssests’. I am trying to further using CDF in my Lab so this is really important to me, thanks again for answering!!!

Hi, if you have the timestamp of your data in the format like “2022-02-10T17:00:00.000Z“, then you can use the to_timestamp function on the column, like to_timestamp(time_stamp). I took a look at the transformation you mentioned above and I could see that the column in RAW was in fact of type string. I think “cast(cast(time_stamp as double)/1000 as timestamp)” should work to cast the column to timestamp.

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