[rrd-users] rrdtool info results

[Samson Martinez]

I'm trying to debug the output of an rrd file because the data results
just don't seem right. I dug into the rrd using the "rrdtool info"
process and received the output listed below. There appear to be more
NaN entries than I thought would be normal. Any ideas what something
like this would indicate? 

Thanks!

-Samson

rrdtool info file.rrd
filename = "file.rrd"
rrd_version = "0001"
step = 300
last_update = 1064499901
ds[in_bytes].type = "ABSOLUTE"
ds[in_bytes].minimal_heartbeat = 400
ds[in_bytes].min = NaN
ds[in_bytes].max = NaN
ds[in_bytes].last_ds = "UNKN"
ds[in_bytes].value = 3.5747508306e+00
ds[in_bytes].unknown_sec = 0
ds[in_pkts].type = "ABSOLUTE"
ds[in_pkts].minimal_heartbeat = 400
ds[in_pkts].min = NaN
ds[in_pkts].max = NaN
ds[in_pkts].last_ds = "UNKN"
ds[in_pkts].value = 5.3156146179e-02
ds[in_pkts].unknown_sec = 0
ds[in_flows].type = "ABSOLUTE"
ds[in_flows].minimal_heartbeat = 400
ds[in_flows].min = NaN
ds[in_flows].max = NaN
ds[in_flows].last_ds = "UNKN"
ds[in_flows].value = 2.3255813953e-02
ds[in_flows].unknown_sec = 0
ds[out_bytes].type = "ABSOLUTE"
ds[out_bytes].minimal_heartbeat = 400
ds[out_bytes].min = NaN
ds[out_bytes].max = NaN
ds[out_bytes].last_ds = "UNKN"
ds[out_bytes].value = 3.2558139535e+00
ds[out_bytes].unknown_sec = 0
ds[out_pkts].type = "ABSOLUTE"
ds[out_pkts].minimal_heartbeat = 400
ds[out_pkts].min = NaN
ds[out_pkts].max = NaN
ds[out_pkts].last_ds = "UNKN"
ds[out_pkts].value = 3.6544850498e-02
ds[out_pkts].unknown_sec = 0
ds[out_flows].type = "ABSOLUTE"
ds[out_flows].minimal_heartbeat = 400
ds[out_flows].min = NaN
ds[out_flows].max = NaN
ds[out_flows].last_ds = "UNKN"
ds[out_flows].value = 3.6544850498e-02
ds[out_flows].unknown_sec = 0
rra[0].cf = "AVERAGE"
rra[0].rows = 600
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[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].pdp_per_row = 6
rra[1].xff = 0.0000000000e+00
rra[1].cdp_prep[0].value = 3.6889417497e+01
rra[1].cdp_prep[0].unknown_datapoints = 0
rra[1].cdp_prep[1].value = 5.0875614618e-01
rra[1].cdp_prep[1].unknown_datapoints = 0
rra[1].cdp_prep[2].value = 3.0245581395e-01
rra[1].cdp_prep[2].unknown_datapoints = 0
rra[1].cdp_prep[3].value = 3.4012080620e+01
rra[1].cdp_prep[3].unknown_datapoints = 0
rra[1].cdp_prep[4].value = 3.8054485050e-01
rra[1].cdp_prep[4].unknown_datapoints = 0
rra[1].cdp_prep[5].value = 3.8054485050e-01
rra[1].cdp_prep[5].unknown_datapoints = 0
rra[2].cf = "AVERAGE"
rra[2].rows = 600
rra[2].pdp_per_row = 24
rra[2].xff = 0.0000000000e+00
rra[2].cdp_prep[0].value = 3.6889417497e+01
rra[2].cdp_prep[0].unknown_datapoints = 0
rra[2].cdp_prep[1].value = 5.0875614618e-01
rra[2].cdp_prep[1].unknown_datapoints = 0
rra[2].cdp_prep[2].value = 3.0245581395e-01
rra[2].cdp_prep[2].unknown_datapoints = 0
rra[2].cdp_prep[3].value = 3.4012080620e+01
rra[2].cdp_prep[3].unknown_datapoints = 0
rra[2].cdp_prep[4].value = 3.8054485050e-01
rra[2].cdp_prep[4].unknown_datapoints = 0
rra[2].cdp_prep[5].value = 3.8054485050e-01
rra[2].cdp_prep[5].unknown_datapoints = 0
rra[3].cf = "AVERAGE"
rra[3].rows = 1827
rra[3].pdp_per_row = 288
rra[3].xff = 0.0000000000e+00
rra[3].cdp_prep[0].value = 4.0956084164e+01
rra[3].cdp_prep[0].unknown_datapoints = 167
rra[3].cdp_prep[1].value = 5.7208947951e-01
rra[3].cdp_prep[1].unknown_datapoints = 167
rra[3].cdp_prep[2].value = 3.2912248062e-01
rra[3].cdp_prep[2].unknown_datapoints = 167
rra[3].cdp_prep[3].value = 3.7025413953e+01
rra[3].cdp_prep[3].unknown_datapoints = 167
rra[3].cdp_prep[4].value = 4.1387818383e-01
rra[3].cdp_prep[4].unknown_datapoints = 167
rra[3].cdp_prep[5].value = 4.1387818383e-01
rra[3].cdp_prep[5].unknown_datapoints = 167
rra[4].cf = "MAX"
rra[4].rows = 600
rra[4].pdp_per_row = 24
rra[4].xff = 0.0000000000e+00
rra[4].cdp_prep[0].value = 1.1682355556e+01
rra[4].cdp_prep[0].unknown_datapoints = 0
rra[4].cdp_prep[1].value = 1.7371111111e-01
rra[4].cdp_prep[1].unknown_datapoints = 0
rra[4].cdp_prep[2].value = 9.3544444444e-02
rra[4].cdp_prep[2].unknown_datapoints = 0
rra[4].cdp_prep[3].value = 1.1356266667e+01
rra[4].cdp_prep[3].unknown_datapoints = 0
rra[4].cdp_prep[4].value = 1.2733333333e-01
rra[4].cdp_prep[4].unknown_datapoints = 0
rra[4].cdp_prep[5].value = 1.2733333333e-01
rra[4].cdp_prep[5].unknown_datapoints = 0
rra[5].cf = "MAX"
rra[5].rows = 1827
rra[5].pdp_per_row = 288
rra[5].xff = 0.0000000000e+00
rra[5].cdp_prep[0].value = 1.1682355556e+01
rra[5].cdp_prep[0].unknown_datapoints = 167
rra[5].cdp_prep[1].value = 1.7371111111e-01
rra[5].cdp_prep[1].unknown_datapoints = 167
rra[5].cdp_prep[2].value = 9.3544444444e-02
rra[5].cdp_prep[2].unknown_datapoints = 167
rra[5].cdp_prep[3].value = 1.1356266667e+01
rra[5].cdp_prep[3].unknown_datapoints = 167
rra[5].cdp_prep[4].value = 1.2733333333e-01
rra[5].cdp_prep[4].unknown_datapoints = 167
rra[5].cdp_prep[5].value = 1.2733333333e-01
rra[5].cdp_prep[5].unknown_datapoints = 167


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