March 1, 2016
With an update each 15sec, the timescale parameters seems a bit limited.
Would be nice to have it completly dynamic and not limited to some values ( actual is 10, 20, ... 720..).
this would allow me to generate graph with different time range always using the same "resolution" by adjusting dynamically the timescale to export the same volume of data.
If it's not possible, could you add 1 mn and 5mn to the timescale ( & even a bit more if you can ).
March 1, 2016
ho another thing, when exporting using timescale parameter, it starts to jump from first value. The problem with that is you always miss the last fresh value then.
Using timescale should timescale from the last values to the first. Missing the first one is mostly less important than the last fresh data.
This also solve some charts api display problem like generating highstock with highchart.js. Missing last data can makes important gaps on the chart navigator bar at loading, and cause nav issue.
March 1, 2016
I hope some TeamSpeak guy will pass here.
I've found a more important issue.
I was wondering why I couldn't get like one month of field data using timescale to preserve bandwidth.
Whatever the TimeScale parameter I use, it only gives me 34 hours of last data ( one data each 15 )
It seems the Timescale filtering is applied after the export limit.
I mean, if you have like 2 102 400 entries in your channel corresponding at sensors updating each 15sec for a year, and you want to grab this year of data with a timescale of 1440, this should gives 1460 entries. Far better than grabing the 2102400 just for generating a year graph.
But you can't because it will filter the last limited entries (looks to be 8000 ) giving only 5 result ( 8000/1440)
There's no sense of having a timescale parameter capable of 1440 if the source data is filtered before to the last 8000 entries.
It should work the other way, first it filters data with timescale from your database, then if there's more than the limit, only deliver the last 8000..
This looks more a bug than a feature, or have I missed something ?
Any input from ThingSpeak devs?
January 18, 2018
I would like to push this issue - as I encountered the same problem.
It's a real pain and API bug that should be fixed.
A simple setup (i assume 1 month has 30 days in average)
- log data for a year in a 15 Min interval.
- try to query a range of one year => you will be limited to 8000 points (8000 points / 96 points[per day]/30 days[per month] = 2.7 months, instead of a year)
- try the logical consequence: reduce the interval to 60 mins (which should give you: 8000 / 24 / 30 = 11.1 months, almost a year)
The real result however is, that you will get the datapoints within a 2.7 months timespan but a lower resolution. So changing the interval parameter does not help you at all to change the length of a plottable timespan.
Could you please have a look at this issue as this heavily limits the useability ?
March 9, 2018
Anything new regarding this weird 8000 points limit behaviour when using timescale/average/median/sum?
Uploading data at 15 second interval, for example to have one year's daily averages data, you'd normally need minimal bandwidth and only one api call for 364 values.
But to get this the way it is implemented now, you'd have to make 365*24*60*4 / 8000 = 263 api calls, each giving you only 1.4 days worth of data - so 263x more connections and A LOT bigger bandwidth use, which is not really feasible way of getting long term averages.
If you upload data only once per minute, you'd still have to make 365*24*60 / 8000 = 66 api calls, each worth 5.5 days of data, only to get one year worth of daily averages. It is practically the same if you want monthly averages that would otherwise only take one api call of 12 data points...
This is really annoying and complicates making longer term averages/comparisons inefficient as it takes a lot of unnecessary internet traffic/thingspeak bandwidth load.
Is there a plan to change this behaviour in near future? Are there any better/more efficient ways to do it?
Thanx and best regards!
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