Year Graphs are Empty

[Djiguidjik]

Hi,

I don't know why but when I select "Last Year" for some graphs the result is -nan and no values are drown on the graph (see the pictures).

But any other time value is OK (for example Last Month on the pic).

Why do you think is causing that ?

Thank you

[Osiris]

rrdtool info output would help.

[Djiguidjik]

Hi,

Here's an example of one of the graph which isn't working ;

Code: Select all

rrd_version = "0003"
step = 60
last_update = 1483958882
header_size = 3488
ds[traffic_in].index = 0
ds[traffic_in].type = "COUNTER"
ds[traffic_in].minimal_heartbeat = 120
ds[traffic_in].min = 0,0000000000e+00
ds[traffic_in].max = 1,0000000000e+09
ds[traffic_in].last_ds = "8551608725795"
ds[traffic_in].value = 1,7559541967e+06
ds[traffic_in].unknown_sec = 0
ds[traffic_out].index = 1
ds[traffic_out].type = "COUNTER"
ds[traffic_out].minimal_heartbeat = 120
ds[traffic_out].min = 0,0000000000e+00
ds[traffic_out].max = 1,0000000000e+09
ds[traffic_out].last_ds = "32960527760"
ds[traffic_out].value = 1,7899344262e+03
ds[traffic_out].unknown_sec = 0
rra[0].cf = "AVERAGE"
rra[0].rows = 10080
rra[0].cur_row = 5503
rra[0].pdp_per_row = 1
rra[0].xff = 0,0000000000e+00
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[1].cf = "AVERAGE"
rra[1].rows = 25920
rra[1].cur_row = 11311
rra[1].pdp_per_row = 5
rra[1].xff = 0,0000000000e+00
rra[1].cdp_prep[0].value = 2,1300455531e+06
rra[1].cdp_prep[0].unknown_datapoints = 0
rra[1].cdp_prep[1].value = 2,7308113707e+03
rra[1].cdp_prep[1].unknown_datapoints = 0
rra[2].cf = "AVERAGE"
rra[2].rows = 9000
rra[2].cur_row = 3588
rra[2].pdp_per_row = 30
rra[2].xff = 0,0000000000e+00
rra[2].cdp_prep[0].value = 9,1954577517e+06
rra[2].cdp_prep[0].unknown_datapoints = 9
rra[2].cdp_prep[1].value = 8,2143788707e+03
rra[2].cdp_prep[1].unknown_datapoints = 9
rra[3].cf = "AVERAGE"
rra[3].rows = 2250
rra[3].cur_row = 1618
rra[3].pdp_per_row = 120
rra[3].xff = 0,0000000000e+00
rra[3].cdp_prep[0].value = 9,1954577517e+06
rra[3].cdp_prep[0].unknown_datapoints = 39
rra[3].cdp_prep[1].value = 8,2143788707e+03
rra[3].cdp_prep[1].unknown_datapoints = 39
rra[4].cf = "AVERAGE"
rra[4].rows = 797
rra[4].cur_row = 639
rra[4].pdp_per_row = 1440
rra[4].xff = 0,0000000000e+00
rra[4].cdp_prep[0].value = 1,5360312255e+08
rra[4].cdp_prep[0].unknown_datapoints = 71
rra[4].cdp_prep[1].value = 5,2283129246e+05
rra[4].cdp_prep[1].unknown_datapoints = 71
rra[5].cf = "MAX"
rra[5].rows = 10080
rra[5].cur_row = 819
rra[5].pdp_per_row = 1
rra[5].xff = 0,0000000000e+00
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[6].cf = "MAX"
rra[6].rows = 25920
rra[6].cur_row = 23255
rra[6].pdp_per_row = 5
rra[6].xff = 0,0000000000e+00
rra[6].cdp_prep[0].value = 8,7028536650e+05
rra[6].cdp_prep[0].unknown_datapoints = 0
rra[6].cdp_prep[1].value = 9,2924367880e+02
rra[6].cdp_prep[1].unknown_datapoints = 0
rra[7].cf = "MAX"
rra[7].rows = 9000
rra[7].cur_row = 398
rra[7].pdp_per_row = 30
rra[7].xff = 0,0000000000e+00
rra[7].cdp_prep[0].value = 1,6180547394e+06
rra[7].cdp_prep[0].unknown_datapoints = 9
rra[7].cdp_prep[1].value = 9,4537644539e+02
rra[7].cdp_prep[1].unknown_datapoints = 9
rra[8].cf = "MAX"
rra[8].rows = 2250
rra[8].cur_row = 1222
rra[8].pdp_per_row = 120
rra[8].xff = 0,0000000000e+00
rra[8].cdp_prep[0].value = 1,6180547394e+06
rra[8].cdp_prep[0].unknown_datapoints = 39
rra[8].cdp_prep[1].value = 9,4537644539e+02
rra[8].cdp_prep[1].unknown_datapoints = 39
rra[9].cf = "MAX"
rra[9].rows = 797
rra[9].cur_row = 699
rra[9].pdp_per_row = 1440
rra[9].xff = 0,0000000000e+00
rra[9].cdp_prep[0].value = 1,6180547394e+06
rra[9].cdp_prep[0].unknown_datapoints = 71
rra[9].cdp_prep[1].value = 9,9628112994e+02
rra[9].cdp_prep[1].unknown_datapoints = 71