进行每天重置的累积功能

时间:2018-12-10 17:55:15

标签: grafana influxdb

我正在记录能源使用情况数据作为计数器,我希望将其显示为每天重置的累积图表,类似于asked here

我可以生成累积值,如下所示:

img {
float: right;
margin:;//here is blank

以及每日价值:

SELECT mean("value") \
  FROM "energy" \
  WHERE $timeFilter \
  GROUP BY time($__interval)

但是我不能减去它或在一个查询中得到它,因为GROUP BY时间是不同的。

(如何)在influxdb中可行?我已经看过INTEGRATE()了,但是还没有找到一种使它起作用的方法。

数据如下所示(示例限制为1天):

SELECT max("value") \
  FROM "energy" \
  WHERE $timeFilter \
  GROUP BY time(1d)

我可以绘制以下内容: Current state

但是我想要类似的东西: Desired output

1 个答案:

答案 0 :(得分:1)

found a solution,最后很简单:

SELECT kaifa-kaifa_fill as Energy FROM
  (SELECT first(kaifa) as kaifa_fill from energyv2 WHERE $timeFilter group by time(1d) TZ('Europe/Amsterdam')),
  (SELECT first(kaifa) as kaifa from energyv2 WHERE $timeFilter GROUP BY time($__interval))
fill(previous)

请注意,必须使用fill(上一个)来确保kaifa_fill和kaifa重叠。

示例数据:

time                 kaifa     kaifa_fill kaifa_kaifa_fill
----                 -----     ---------- ----------------
2019-08-03T00:00:00Z 179688195 179688195  0
2019-08-03T01:00:00Z 179746833 179688195  58638
2019-08-03T02:00:00Z 179803148 179688195  114953
2019-08-03T03:00:00Z 179859464 179688195  171269
2019-08-03T04:00:00Z 179914038 179688195  225843
2019-08-03T05:00:00Z 179967450 179688195  279255
2019-08-03T06:00:00Z 179905910 179688195  217715
2019-08-03T07:00:00Z 179847272 179688195  159077
2019-08-03T08:00:00Z 179698065 179688195  9870
2019-08-03T09:00:00Z 179378170 179688195  -310025
2019-08-03T10:00:00Z 179341013 179688195  -347182
2019-08-03T11:00:00Z 179126201 179688195  -561994
2019-08-03T12:00:00Z 179039116 179688195  -649079
2019-08-03T13:00:00Z 178935193 179688195  -753002
2019-08-03T14:00:00Z 178687870 179688195  -1000326
2019-08-03T15:00:00Z 178517762 179688195  -1170433
2019-08-03T16:00:00Z 178409776 179688195  -1278420
2019-08-03T17:00:00Z 178376102 179688195  -1312093
2019-08-03T18:00:00Z 178388875 179688195  -1299320
2019-08-03T19:00:00Z 178780181 179688195  -908015
2019-08-03T20:00:00Z 178928226 179688195  -759969
2019-08-03T21:00:00Z 179065241 179688195  -622954
2019-08-03T22:00:00Z 179183098 179688195  -505098
2019-08-03T23:00:00Z 179306179 179688195  -382016
2019-08-04T00:00:00Z 179306179 179370042  -63863
2019-08-04T00:00:00Z 179370042 179370042  0
2019-08-04T01:00:00Z 179417649 179370042  47607
2019-08-04T02:00:00Z 179464094 179370042  94053
2019-08-04T03:00:00Z 179509960 179370042  139918
2019-08-04T04:00:00Z 179591820 179370042  221779
2019-08-04T05:00:00Z 179872817 179370042  502775
2019-08-04T06:00:00Z 180056278 179370042  686236
2019-08-04T07:00:00Z 179929713 179370042  559671
2019-08-04T08:00:00Z 179514604 179370042  144562
2019-08-04T09:00:00Z 179053049 179370042  -316992
2019-08-04T10:00:00Z 178683225 179370042  -686817
2019-08-04T11:00:00Z 178078269 179370042  -1291773
2019-08-04T12:00:00Z 177650387 179370042  -1719654
2019-08-04T13:00:00Z 177281724 179370042  -2088317
2019-08-04T14:00:00Z 177041367 179370042  -2328674
2019-08-04T15:00:00Z 176807397 179370042  -2562645
2019-08-04T16:00:00Z 176737148 179370042  -2632894
2019-08-04T17:00:00Z 176677349 179370042  -2692693
2019-08-04T18:00:00Z 176690702 179370042  -2679340
2019-08-04T19:00:00Z 176734825 179370042  -2635216
2019-08-04T20:00:00Z 176810300 179370042  -2559742
2019-08-04T21:00:00Z 176866035 179370042  -2504007
2019-08-04T22:00:00Z 176914803 179370042  -2455239
2019-08-04T23:00:00Z 176965893 179370042  -2404149
2019-08-05T00:00:00Z 176965893 177016983  -51090
2019-08-05T00:00:00Z 177016983 177016983  0

示例图:

Sawtooth plotting in Grafana and influxdb