Hi Alex, Thank you for your detailed reply which has certainly helped me understand RRA calculations a bit better.
However I am only using one RRA (I should have pointed this out in my first post): filename = "noise.rrd" rrd_version = "0003" step = 30 last_update = 1313098265 ds[noise].type = "GAUGE" ds[noise].minimal_heartbeat = 60 ds[noise].min = NaN ds[noise].max = NaN ds[noise].last_ds = "9.4" ds[noise].value = 5.6364270600e+01 ds[noise].unknown_sec = 0 rra[0].cf = "AVERAGE" rra[0].rows = 5760 rra[0].cur_row = 4995 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 Does this influence your previous reply? Thanks, Oliver. -----Original Message----- From: Alex van den Bogaerdt Sent: Tuesday, August 09, 2011 2:00 PM To: rrd-users@lists.oetiker.ch Subject: Re: [rrd-users] VDEF MINIMUM You are looking at averages. Your two tests use different RRAs. For instance: one RRA consolidates 1 PDP into 1 CDP, the other consolidates 3 PDPs into one CDP. Look at 10,20,30,40,50,60. One RRA has all 6 values, the other RRA has average(10,20,30) equals 20, average(40,50,60) equals 50. minimum(10,20,30,40,50,60) equals 10. minimum(20,50) equals 20. Your test would return 10 and 20. It should work much better if you look at minimums of minimums: The other RRA would contain min(10,20,30) equals 10, min(40,50,60) equals 40. Then min(10,20,30,40,50,60) and min(10,40) both return 10. There can be two places where consolidation takes place. One is when data is copied into RRAs, the other is when rrdtool graph needs data in a resolution which is not available. If you take both into account, you should be able to get predictable results. HTH Alex _______________________________________________ rrd-users mailing list rrd-users@lists.oetiker.ch https://lists.oetiker.ch/cgi-bin/listinfo/rrd-users