Hi Sean,

Sorry but I don't think that works either in the general case as it relies
on knowing in advance that I am going to want to graph this with 1h
resolution.   In reality, when someone is viewing data for the last 10m I
will want to graph with 5s resolution, when they're viewing the last 24h I
might want to graph with 10m resolution etc.

I really need the ability to calculate the mean within each series
dynamically at a scope that matches the resolution I am graphing over and
then to sum across series.   At the moment I'm thinking that I might have
to move away from InfluxDB to Graphite which provides this kind of
flexibility.   I don't know anything about the implemention of InfluxDB --
is the kind of capability that I need here something that would
fundamentally be hard to add?

Thanks!

Mat

On 26 June 2016 at 22:34, Sean Beckett <[email protected]> wrote:

> So you want the sum of the mean?
>
> First write a continuous query
> <https://docs.influxdata.com/influxdb/v0.13/query_language/continuous_queries/>
> to calculate the MEAN, as in my prior query, and write it back to a new
> measurement. Then you can query that measurement for the sum.
>
> E.g.
>
> CREATE CONTINUOUS QUERY foo ON mydb REPEAT EVERY 15m FOR 2h BEGIN
>  SELECT MEAN(value) INTO sipMessagesMean FROM sipMessages GROUP BY
> time(1h), *
> END
>
> Then
>
> SELECT SUM(mean) FROM sipMessagesMean WHERE time > now() -7d GROUP BY
> time(1h), tag_message_type
>
> On Sat, Jun 25, 2016 at 4:43 AM, Mat and Helen <[email protected]>
> wrote:
>
>> Thanks Sean.  Unfortunately that's not what I need -- I need the TOTAL
>> rate that SIP messages are being processed across the deployment.   So I
>> need to SUM across the nodes.   I think your formula gives me the average
>> rate per node?
>>
>> Mat
>>
>> On 24 June 2016 at 21:17, Sean Beckett <[email protected]> wrote:
>>
>>> It seems that
>>>
>>> SELECT MEAN(value) FROM sipMessages WHERE time > now() -7d GROUP BY
>>> time(1h), tag_message_type
>>>
>>> would return what you want. That will give the average of the "value"
>>> field per hour, per message_type, but across all nodes. If that isn't what
>>> you want, can you clarify why not?
>>>
>>> On Fri, Jun 24, 2016 at 2:57 AM, <[email protected]> wrote:
>>>
>>>> I've hit an issue that I think, sadly, is going to prevent us from
>>>> deploying InfluxDB.   The following is an example of this issue, but in
>>>> reality it manifests in different ways in many of our use cases.
>>>>
>>>> I have a set of nodes each reporting the rate at which differnet SIP
>>>> messages are being received (in terms of messages per s)
>>>>
>>>> timestamp | tag_node | tag_message_type   |  value
>>>> ---------------------------------------------------
>>>>           | node1    | INVITE             | 1728
>>>>           | node1    | BYE                | 1051
>>>>           | node2    | INVITE             | 1521
>>>>           | node2    | BYE                | 1241
>>>>
>>>> Each node reports writes these stats to InfluxDB roughly every 5s.
>>>>
>>>> I want to draw charts showing the total rate of different types of SIP
>>>> messages being processed across my deployment, split by message_type.
>>>>
>>>> Ideally I would do this like so:
>>>>
>>>> SELECT sum("value") FROM "sipMessages" WHERE  WHERE time > now() - 7d
>>>> GROUP BY time(1h), "tag_message_type"
>>>>
>>>> The problem here is that this sums across different values of node, but
>>>> also sums multiple points within each series.  So the number I get returned
>>>> is ~720 times higher than it should be.   If I knew that there were always
>>>> going to be exactly 720 measurements in each time interval I could divide
>>>> by 720, but this 720 is only an approximation.   [it is also the case that
>>>> using Grafana to draw the graphs this "1h" period changes automatically
>>>> based on the period that I'm graphing over]
>>>>
>>>> What I really need to do is to run an average aggregation within each
>>>> series over each GROUP BY time period (so that for each node / message_type
>>>> combination I have one data point per time period), and then sum the
>>>> results of those aggregations across the different series.
>>>>
>>>> I don't believe this is possibe though, and I can't see any way to work
>>>> around it?
>>>>
>>>> What I don't understand is why this isn't a critical issue for lots of
>>>> users as this seems like a very standard use case.   Is there a reason that
>>>> other users are able to avoid this issue?
>>>>
>>>> Would adding this capability (to do per series aggregation within
>>>> "GROUP BY time" intervals) be technically difficult?
>>>>
>>>> --
>>>> Remember to include the InfluxDB version number with all issue reports
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>>>>
>>>
>>>
>>>
>>> --
>>> Sean Beckett
>>> Director of Support and Professional Services
>>> InfluxDB
>>>
>>> --
>>> Remember to include the InfluxDB version number with all issue reports
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>>
>> --
>> Remember to include the InfluxDB version number with all issue reports
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>>
>> For more options, visit https://groups.google.com/d/optout.
>>
>
>
>
> --
> Sean Beckett
> Director of Support and Professional Services
> InfluxDB
>
> --
> Remember to include the InfluxDB version number with all issue reports
> ---
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>
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