Only 50 hours of data stored

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drlizau
Posts: 8
Joined: Sat Mar 14, 2009 10:39 pm

Only 50 hours of data stored

#1 Post by drlizau » Sat May 18, 2019 5:52 pm

I've had a Cacti install running on Debian for years, and a few upgrades. After one upgrade I found that new RRAs would only store a little over 50 hours of data. Although I've upgraded further and tried to investigate, I haven't solved this problem.

Can someone advise me on what I can do to have the data for an entire year rather than 2 days?

OS
Linux banksia 4.9.0-3-686-pae #1 SMP Debian 4.9.30-2+deb9u2 (2017-06-26) i686 GNU/Linux
$ lsb_release -a
No LSB modules are available.
Distributor ID: Debian
Description: Debian GNU/Linux 9.8 (stretch)
Release: 9.8
Codename: stretch


CACTI

0.8.8h

RRD
RRDtool 1.6.0 Copyright by Tobias Oetiker <[email protected]>
Compiled 2016-04-25 07:23:34

I made a new Data Input Method to duplicate one of my existing ones with this problem. It has now been running for a week, and again some of the data is for 50 hours only, but very oddly, one item is showing for the entire week.
The graph is at https://www.billiau.net/cacti/graph.php ... ph_id=137
$ rrdtool info /var/lib/cacti/rra/energy_119.rrd

Code: Select all

filename = "/var/lib/cacti/rra/energy_119.rrd"
rrd_version = "0003"
step = 300
last_update = 1558218603
header_size = 7432
ds[temp_3].index = 0
ds[temp_3].type = "GAUGE"
ds[temp_3].minimal_heartbeat = 600
ds[temp_3].min = 0.0000000000e+00
ds[temp_3].max = NaN
ds[temp_3].last_ds = "68.7"
ds[temp_3].value = 2.0610000000e+02
ds[temp_3].unknown_sec = 0
ds[temp_1].index = 1
ds[temp_1].type = "GAUGE"
ds[temp_1].minimal_heartbeat = 600
ds[temp_1].min = 0.0000000000e+00
ds[temp_1].max = NaN
ds[temp_1].last_ds = "16.400000000000002"
ds[temp_1].value = 4.9200000000e+01
ds[temp_1].unknown_sec = 0
ds[temp_2].index = 2
ds[temp_2].type = "GAUGE"
ds[temp_2].minimal_heartbeat = 600
ds[temp_2].min = 0.0000000000e+00
ds[temp_2].max = 1.2000000000e+02
ds[temp_2].last_ds = "13.200000000000001"
ds[temp_2].value = 3.9600000000e+01
ds[temp_2].unknown_sec = 0
ds[relay_2_gas].index = 3
ds[relay_2_gas].type = "GAUGE"
ds[relay_2_gas].minimal_heartbeat = 600
ds[relay_2_gas].min = 0.0000000000e+00
ds[relay_2_gas].max = 1.0000000000e+02
ds[relay_2_gas].last_ds = "0"
ds[relay_2_gas].value = 0.0000000000e+00
ds[relay_2_gas].unknown_sec = 0
ds[energy].index = 4
ds[energy].type = "GAUGE"
ds[energy].minimal_heartbeat = 600
ds[energy].min = 0.0000000000e+00
ds[energy].max = NaN
ds[energy].last_ds = "0"
ds[energy].value = 0.0000000000e+00
ds[energy].unknown_sec = 0
ds[relay_1_pump].index = 5
ds[relay_1_pump].type = "GAUGE"
ds[relay_1_pump].minimal_heartbeat = 600
ds[relay_1_pump].min = 0.0000000000e+00
ds[relay_1_pump].max = 1.0000000000e+02
ds[relay_1_pump].last_ds = "0"
ds[relay_1_pump].value = 0.0000000000e+00
ds[relay_1_pump].unknown_sec = 0
rra[0].cf = "AVERAGE"
rra[0].rows = 500
rra[0].cur_row = 89
rra[0].pdp_per_row = 1
rra[0].xff = 5.0000000000e-01
rra[0].cdp_prep[0].value = NaN
rra[0].cdp_prep[0].unknown_datapoints = 0
rra[0].cdp_prep[1].value = NaN
rra[0].cdp_prep[1].unknown_datapoints = 0
rra[0].cdp_prep[2].value = NaN
rra[0].cdp_prep[2].unknown_datapoints = 0
rra[0].cdp_prep[3].value = NaN
rra[0].cdp_prep[3].unknown_datapoints = 0
rra[0].cdp_prep[4].value = NaN
rra[0].cdp_prep[4].unknown_datapoints = 0
rra[0].cdp_prep[5].value = NaN
rra[0].cdp_prep[5].unknown_datapoints = 0
rra[1].cf = "AVERAGE"
rra[1].rows = 600
rra[1].cur_row = 338
rra[1].pdp_per_row = 1
rra[1].xff = 5.0000000000e-01
rra[1].cdp_prep[0].value = NaN
rra[1].cdp_prep[0].unknown_datapoints = 0
rra[1].cdp_prep[1].value = NaN
rra[1].cdp_prep[1].unknown_datapoints = 0
rra[1].cdp_prep[2].value = NaN
rra[1].cdp_prep[2].unknown_datapoints = 0
rra[1].cdp_prep[3].value = NaN
rra[1].cdp_prep[3].unknown_datapoints = 0
rra[1].cdp_prep[4].value = NaN
rra[1].cdp_prep[4].unknown_datapoints = 0
rra[1].cdp_prep[5].value = NaN
rra[1].cdp_prep[5].unknown_datapoints = 0
rra[2].cf = "AVERAGE"
rra[2].rows = 700
rra[2].cur_row = 438
rra[2].pdp_per_row = 6
rra[2].xff = 5.0000000000e-01
rra[2].cdp_prep[0].value = 0.0000000000e+00
rra[2].cdp_prep[0].unknown_datapoints = 0
rra[2].cdp_prep[1].value = 0.0000000000e+00
rra[2].cdp_prep[1].unknown_datapoints = 0
rra[2].cdp_prep[2].value = 0.0000000000e+00
rra[2].cdp_prep[2].unknown_datapoints = 0
rra[2].cdp_prep[3].value = 0.0000000000e+00
rra[2].cdp_prep[3].unknown_datapoints = 0
rra[2].cdp_prep[4].value = 0.0000000000e+00
rra[2].cdp_prep[4].unknown_datapoints = 0
rra[2].cdp_prep[5].value = 0.0000000000e+00
rra[2].cdp_prep[5].unknown_datapoints = 0
rra[3].cf = "AVERAGE"
rra[3].rows = 775
rra[3].cur_row = 712
rra[3].pdp_per_row = 24
rra[3].xff = 5.0000000000e-01
rra[3].cdp_prep[0].value = 4.1240066667e+02
rra[3].cdp_prep[0].unknown_datapoints = 0
rra[3].cdp_prep[1].value = 9.5589333333e+01
rra[3].cdp_prep[1].unknown_datapoints = 0
rra[3].cdp_prep[2].value = 7.8698666667e+01
rra[3].cdp_prep[2].unknown_datapoints = 0
rra[3].cdp_prep[3].value = 0.0000000000e+00
rra[3].cdp_prep[3].unknown_datapoints = 0
rra[3].cdp_prep[4].value = 0.0000000000e+00
rra[3].cdp_prep[4].unknown_datapoints = 0
rra[3].cdp_prep[5].value = 0.0000000000e+00
rra[3].cdp_prep[5].unknown_datapoints = 0
rra[4].cf = "AVERAGE"
rra[4].rows = 800
rra[4].cur_row = 720
rra[4].pdp_per_row = 288
rra[4].xff = 5.0000000000e-01
rra[4].cdp_prep[0].value = 1.8925513667e+04
rra[4].cdp_prep[0].unknown_datapoints = 0
rra[4].cdp_prep[1].value = 1.1833139333e+04
rra[4].cdp_prep[1].unknown_datapoints = 0
rra[4].cdp_prep[2].value = 1.0444946333e+04
rra[4].cdp_prep[2].unknown_datapoints = 0
rra[4].cdp_prep[3].value = 0.0000000000e+00
rra[4].cdp_prep[3].unknown_datapoints = 0
rra[4].cdp_prep[4].value = 0.0000000000e+00
rra[4].cdp_prep[4].unknown_datapoints = 0
rra[4].cdp_prep[5].value = 1.7013333333e+03
rra[4].cdp_prep[5].unknown_datapoints = 0
rra[5].cf = "MAX"
rra[5].rows = 500
rra[5].cur_row = 354
rra[5].pdp_per_row = 1
rra[5].xff = 5.0000000000e-01
rra[5].cdp_prep[0].value = NaN
rra[5].cdp_prep[0].unknown_datapoints = 0
rra[5].cdp_prep[1].value = NaN
rra[5].cdp_prep[1].unknown_datapoints = 0
rra[5].cdp_prep[2].value = NaN
rra[5].cdp_prep[2].unknown_datapoints = 0
rra[5].cdp_prep[3].value = NaN
rra[5].cdp_prep[3].unknown_datapoints = 0
rra[5].cdp_prep[4].value = NaN
rra[5].cdp_prep[4].unknown_datapoints = 0
rra[5].cdp_prep[5].value = NaN
rra[5].cdp_prep[5].unknown_datapoints = 0
rra[6].cf = "MAX"
rra[6].rows = 600
rra[6].cur_row = 156
rra[6].pdp_per_row = 1
rra[6].xff = 5.0000000000e-01
rra[6].cdp_prep[0].value = NaN
rra[6].cdp_prep[0].unknown_datapoints = 0
rra[6].cdp_prep[1].value = NaN
rra[6].cdp_prep[1].unknown_datapoints = 0
rra[6].cdp_prep[2].value = NaN
rra[6].cdp_prep[2].unknown_datapoints = 0
rra[6].cdp_prep[3].value = NaN
rra[6].cdp_prep[3].unknown_datapoints = 0
rra[6].cdp_prep[4].value = NaN
rra[6].cdp_prep[4].unknown_datapoints = 0
rra[6].cdp_prep[5].value = NaN
rra[6].cdp_prep[5].unknown_datapoints = 0
rra[7].cf = "MAX"
rra[7].rows = 700
rra[7].cur_row = 371
rra[7].pdp_per_row = 6
rra[7].xff = 5.0000000000e-01
rra[7].cdp_prep[0].value = -inf
rra[7].cdp_prep[0].unknown_datapoints = 0
rra[7].cdp_prep[1].value = -inf
rra[7].cdp_prep[1].unknown_datapoints = 0
rra[7].cdp_prep[2].value = -inf
rra[7].cdp_prep[2].unknown_datapoints = 0
rra[7].cdp_prep[3].value = -inf
rra[7].cdp_prep[3].unknown_datapoints = 0
rra[7].cdp_prep[4].value = -inf
rra[7].cdp_prep[4].unknown_datapoints = 0
rra[7].cdp_prep[5].value = -inf
rra[7].cdp_prep[5].unknown_datapoints = 0
rra[8].cf = "MAX"
rra[8].rows = 775
rra[8].cur_row = 254
rra[8].pdp_per_row = 24
rra[8].xff = 5.0000000000e-01
rra[8].cdp_prep[0].value = 6.8800000000e+01
rra[8].cdp_prep[0].unknown_datapoints = 0
rra[8].cdp_prep[1].value = 1.6397333333e+01
rra[8].cdp_prep[1].unknown_datapoints = 0
rra[8].cdp_prep[2].value = 1.3198666667e+01
rra[8].cdp_prep[2].unknown_datapoints = 0
rra[8].cdp_prep[3].value = 0.0000000000e+00
rra[8].cdp_prep[3].unknown_datapoints = 0
rra[8].cdp_prep[4].value = 0.0000000000e+00
rra[8].cdp_prep[4].unknown_datapoints = 0
rra[8].cdp_prep[5].value = 0.0000000000e+00
rra[8].cdp_prep[5].unknown_datapoints = 0
rra[9].cf = "MAX"
rra[9].rows = 800
rra[9].cur_row = 762
rra[9].pdp_per_row = 288
rra[9].xff = 5.0000000000e-01
rra[9].cdp_prep[0].value = 7.2187000000e+01
rra[9].cdp_prep[0].unknown_datapoints = 0
rra[9].cdp_prep[1].value = 8.0522000000e+01
rra[9].cdp_prep[1].unknown_datapoints = 0
rra[9].cdp_prep[2].value = 7.0494000000e+01
rra[9].cdp_prep[2].unknown_datapoints = 0
rra[9].cdp_prep[3].value = 0.0000000000e+00
rra[9].cdp_prep[3].unknown_datapoints = 0
rra[9].cdp_prep[4].value = 0.0000000000e+00
rra[9].cdp_prep[4].unknown_datapoints = 0
rra[9].cdp_prep[5].value = 1.0000000000e+02
rra[9].cdp_prep[5].unknown_datapoints = 0
notes: the air temp intermittent graphing is a separate problem, not related to Cacti or RRD Tool. Datasource 'energy' returns zero each reading.
and for those who want to know what this actually shows, it is temperature records for a solar hot water service with a gas booster.

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