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 >>> --- >>> You received this message because you are subscribed to the Google >>> Groups "InfluxDB" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to [email protected]. >>> To post to this group, send email to [email protected]. >>> Visit this group at https://groups.google.com/group/influxdb. >>> To view this discussion on the web visit >>> https://groups.google.com/d/msgid/influxdb/c7be9920-759c-49e5-a23f-a4800c18b979%40googlegroups.com >>> . >>> 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 >> --- >> You received this message because you are subscribed to a topic in the >> Google Groups "InfluxDB" group. >> To unsubscribe from this topic, visit >> https://groups.google.com/d/topic/influxdb/uXdYy9JA6_E/unsubscribe. >> To unsubscribe from this group and all its topics, send an email to >> [email protected]. >> To post to this group, send email to [email protected]. >> Visit this group at https://groups.google.com/group/influxdb. >> To view this discussion on the web visit >> https://groups.google.com/d/msgid/influxdb/CALGqCvPvaBsKuruQ5j1mXtftTo70R7LjYm%2BTNq43QBwCRtzwZA%40mail.gmail.com >> <https://groups.google.com/d/msgid/influxdb/CALGqCvPvaBsKuruQ5j1mXtftTo70R7LjYm%2BTNq43QBwCRtzwZA%40mail.gmail.com?utm_medium=email&utm_source=footer> >> . >> >> For more options, visit https://groups.google.com/d/optout. >> > > -- > Remember to include the InfluxDB version number with all issue reports > --- > You received this message because you are subscribed to the Google Groups > "InfluxDB" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > Visit this group at https://groups.google.com/group/influxdb. > To view this discussion on the web visit > https://groups.google.com/d/msgid/influxdb/CAKyPxTQQsnLyC%3DV_KOJTdRvSA9n1fNtGwm7v63TmH7mScy0YBw%40mail.gmail.com > <https://groups.google.com/d/msgid/influxdb/CAKyPxTQQsnLyC%3DV_KOJTdRvSA9n1fNtGwm7v63TmH7mScy0YBw%40mail.gmail.com?utm_medium=email&utm_source=footer> > . > > 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 --- You received this message because you are subscribed to the Google Groups "InfluxDB" group. 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