I'm trying to leverage my moderate SQL-knowledge for InfluxQL, but I'm missing something(s) about the nature of timeseries db.
Use case
I write a measurements from our issue tracker, when an issue is updated:
issue_updated,project=facebook,ticket=fb1,assignee=coolman status="todo"
Problem
Given this returns rows of issues statuses:
SELECT status
FROM "issue_updated"
If this was SQL (fiddle) I would use COUNT(and then add the WHERE time > NOW() - 1Y GROUP BY time(5m)). However the following gives me Mixing aggregate and non-aggregate queries is not supported
SELECT status, count(status) as 'Count'
FROM "issue_updated"
Can someone give some guidance here? ta
Sounds like what you're looking for is the ability to group by a field value which isn't currently supported.
From what I can tell, if you modify your schema a bit, it should be possible to do what you're looking. Instead of
issue_updated,project=facebook,ticket=fb1,assignee=coolman status="todo"
Do
issue_updated,project=facebook,ticket=fb1,assignee=coolman,status=todo value=1
then
SELECT count(value) FROM "issue_updated" WHERE time > now() - 52w GROUP BY status
name: issue_updated
tags: status=other
time count
---- -----
1449523659065350722 1
name: issue_updated
tags: status=todo
time count
---- -----
1449523659065350722 2
should work.
Related
I have a few points that I am trying to remove that came from bad data and keep reading that you can't really do it but find it hard to believe you really can't.
They have no tags so I tried to give them tags by overwriting them with a tag, then deleting the tag, but it didn't overwrite and i just deleted the new tagged values.
I have the time so tried to delete with where time = 'x' but get a 400 from Chronograf, tried again in Influx CLI with DELETE FROM "apps" where time = '2019-05-01T17:45:00Z' and it runs with no errors, but doesn't actually delete the point.
I understand that because of the way Influx indexes things you can't delete based on fields, but there has to be a way?
Thanks.
I haven't seen explicit examples on deleting series with no tags in official Influxdata docs. But approach like in example below worked for me in test - it drops all series in measurement demo with empty tags. Be careful to include all possible measurement tag names in where clause or you risk to drop good data too.
> drop measurement demo
> select * from demo
> insert demo,tagA=A,tagB=B value=5 123455
> insert demo,tagA=A value=6 123456
> insert demo value=1 123451
> insert demo value=2 123452
> insert demo value=3 123453
> select * from demo
name: demo
time tagA tagB value
---- ---- ---- -----
123451 1
123452 2
123453 3
123455 A B 5
123456 A 6
> drop series from demo where tagA='' and tagB=''
> select * from demo
name: demo
time tagA tagB value
---- ---- ---- -----
123455 A B 5
123456 A 6
I'd like to calculate the delta values for a series of measurements stored in an InfluxDB. The values are readings from an electricity meter taken every 5 minutes. The values increase over time. Here is subset of the data to give you an idea (commands shown below are executed in the InfluxDB CLI):
> SELECT "Haushaltstromzaehler - cnt" FROM "myhome_measurements" WHERE time >= '2018-02-02T10:00:00Z' AND time < '2018-02-02T11:00:00Z'
name: myhome_measurements
time Haushaltstromzaehler - cnt
---- --------------------------
2018-02-02T10:00:12.610811904Z 11725.638
2018-02-02T10:05:11.242021888Z 11725.673
2018-02-02T10:10:10.689827072Z 11725.707
2018-02-02T10:15:12.143326976Z 11725.736
2018-02-02T10:20:10.753357056Z 11725.768
2018-02-02T10:25:11.18448512Z 11725.803
2018-02-02T10:30:12.922032896Z 11725.837
2018-02-02T10:35:10.618788096Z 11725.867
2018-02-02T10:40:11.820355072Z 11725.9
2018-02-02T10:45:11.634203904Z 11725.928
2018-02-02T10:50:11.10436096Z 11725.95
2018-02-02T10:55:10.753853952Z 11725.973
Calculating the differences in the InfluxDB CLI is pretty straightforward with the difference() function. This gives me the electricity consumed within the 5 minutes intervals:
> SELECT difference("Haushaltstromzaehler - cnt") FROM "myhome_measurements" WHERE time >= '2018-02-02T10:00:00Z' AND time < '2018-02-02T11:00:00Z'
name: myhome_measurements
time difference
---- ----------
2018-02-02T10:05:11.242021888Z 0.03499999999985448
2018-02-02T10:10:10.689827072Z 0.033999999999650754
2018-02-02T10:15:12.143326976Z 0.02900000000045111
2018-02-02T10:20:10.753357056Z 0.0319999999992433
2018-02-02T10:25:11.18448512Z 0.03499999999985448
2018-02-02T10:30:12.922032896Z 0.033999999999650754
2018-02-02T10:35:10.618788096Z 0.030000000000654836
2018-02-02T10:40:11.820355072Z 0.03299999999944703
2018-02-02T10:45:11.634203904Z 0.028000000000247383
2018-02-02T10:50:11.10436096Z 0.02200000000084401
2018-02-02T10:55:10.753853952Z 0.02299999999922875
Where I struggle is getting this to work in a continuous query. Here is the command I used to setup the continuous query:
CREATE CONTINUOUS QUERY cq_Haushaltstromzaehler_cnt ON myhomedb
BEGIN
SELECT difference(sum("Haushaltstromzaehler - cnt")) AS "delta" INTO "Haushaltstromzaehler_delta" FROM "myhome_measurements" GROUP BY time(1h)
END
Looking in the InfluxDB log file I see that no data is written in the new 'delta' measurement from the continuous query execution:
...finished continuous query cq_Haushaltstromzaehler_cnt, 0 points(s) written...
After much troubleshooting and experimenting I now understand why no data is generated. Setting up a continuous query requires to use the GROUP BY time() statement. This in turn requires to use an aggregate function within the differences() function. The problem now is that the aggregate function returns only one value for the time period specified by GROUP BY time(). Obviously, the differences() function cannot calculate a difference from just one value. Essentially, continuous query executes a command like this:
> SELECT difference(sum("Haushaltstromzaehler - cnt")) FROM "myhome_measurements" WHERE time >= '2018-02-02T10:00:00Z' AND time < '2018-02-02T11:00:00Z' GROUP BY time(1h)
>
I'm now somewhat clueless as to how to make this work and appreciate any advice you might have.
Does it help using the last aggregate function? Not tested this as a cq yet.
Select difference(last(T1_Consumed)) AS T1_Delta, difference(last(T2_Consumed)) AS T2_Delta
from P1Data
where time >= 1551648871000000000 group by time(1h)
DIFFERENCE() would calculate delta from the "aggregated" value taken from previous group, not within current group.
So fill free to use selector function there - since your counters seemed to be cumulative, LAST() should be working well.
select SUM(value)
from /measurment1|measurment2/
where time > now() - 60m and host = 'hostname' limit 2;
Name: measurment1
time sum
---- ---
1505749307008583382 4680247
name: measurment2
time sum
---- ---
1505749307008583382 3004489
But is it possible to get value of SUM(measurment1+measurment2) , so that I see only o/p .
Not possible in influx query language. It does not support functions across measurements.
If this is something you require, you may be interested in layering another API on top of influx that do this, like Graphite via Influxgraph.
For the above, something like this.
/etc/graphite-api.yaml:
finders:
- influxgraph.InfluxDBFinder
influxdb:
db: <your database>
templates:
# Produces metric paths like 'measurement1.hostname.value'
- measurement.host.field*
Start the graphite-api/influxgraph webapp.
A query /render?from=-60min&target=sum(*.hostname.value) then produces the sum of value on tag host='hostname' for all measurements.
{measurement1,measurement2}.hostname.value can be used instead to limit it to specific measurements.
NB - Performance wise (of influx), best to have multiple values in the same measurement rather than same value field name in multiple measurements.
I have a following issue:
I need to calculate difference between consecutive points where some arbitrary ID is equal. The following:
SELECT difference(value_field) FROM mesurementName WHERE "IdField" = '10'
Works, returns difference between each consecutive point with IdField BUT IdField is lost (only time is propagated to query result). In my case time is not unique (i.e. measurement may contain many points with same timestamp, but different IdField). So I tried:
SELECT difference(value_field), IdField FROM mesurementName WHERE "IdField" = '10'
which yields:
error parsing query: mixing aggregate and non-aggregate queries is not supported!!
My next attempt was using sub-query:
SELECT IdField, diff
FROM (
SELECT
difference(flow_val) as diff
FROM
mesurementA
WHERE "IdField" = '10'
)
Which resulted in always null value in IdField.
I'd like to ask you for help or suggestion how to solve issue. By the way, we are using InfluxDB 1.3, which is not supporting JOIN anymore
If anyone would stuck as I was, then solution is following:
SELECT difference(value_field) FROM mesurementName GROUP BY "IdField"
Above somehow implicitly add "IdField" to result series and is propagated to resulting measurements with INTO clause
I have a basic Esper query as follows:
#Name("MyTestQuery")
#Description("My First Test Query")
select sum(qty), venue
from MyTestWindow
group by venue
The query seems to duplicate the results of my sum i.e. if I send in a qty of 10 my query will fire multiple times and output:
10, 20, 30, 40
However, if I remove the group by function then it just outputs 10.
Is anyone able to advise why this might happen?
Typically you need to qualify the Stream name (MyTestWindow) with a window, so it is
"from MyTestWindow.win:time(1 sec) ". You need to select an appropriate window type from many Epser offers, depending on your application.
This example:
select sum(qty), venue
from MyTestWindow.win:time_batch(1 sec)
group by venue
having sum(qty) is not null
You can run a simple test of this at http://esper-epl-tryout.appspot.com/epltryout/mainform.html
the best way of doing a group by is to trigger an artificial "event" after sending in all events. this way you can fully control what you want you want to output and not let Esper's engine run in real time.
You might have to use the "distinct" feature in select to avoid duplicates. Esper can sometimes create duplicate events when you aren't using trigger variables, so distinct will allow you to get rid of unwanted events.
You can use win:time_batch to specified time interval in one update and coalesce function to handle the null value
select venue, sum(coalesce(ty, 0))
from MyTestWindow.win:time_batch(1 sec)
group by venue