| 1 |
#! /usr/bin/env python |
| 2 |
# $Id$ |
| 3 |
# Source: $URL$ |
| 4 |
# J. A. Templon, NIKHEF/PDP 2011 |
| 5 |
|
| 6 |
import optparse |
| 7 |
|
| 8 |
p = optparse.OptionParser(description="Program to make rrdtool plots " + \ |
| 9 |
"of job running jobs by unix group") |
| 10 |
|
| 11 |
# p.add_option("-r",action="store",dest="minsize",default='0',help="minimum size of dirs considered; can use suffixes k,M,G for multiples of 1000**{1,2,3} bytes") |
| 12 |
# p.add_option("--qdel",action="store_true",dest="deljobs",help="delete jobs for which TMPDIR is larger than MINSIZE",default=False) |
| 13 |
|
| 14 |
p.add_option("--rank-only",action="store_true",dest="rankonly", |
| 15 |
help="don't plot, just print ranking of groups",default=False) |
| 16 |
|
| 17 |
debug = 0 |
| 18 |
|
| 19 |
opts, args = p.parse_args() |
| 20 |
|
| 21 |
import os |
| 22 |
|
| 23 |
NUMGROUPS=8 |
| 24 |
DATADIR=os.environ['HOME'] + '/ndpfdata/' |
| 25 |
PLOTDIR=os.environ['HOME'] + '/public_html/' |
| 26 |
# 8 class qualitative paired color scheme |
| 27 |
|
| 28 |
colors = [ "#A6CEE3", "#1F77B4", "#B2DF8A", "#33A02C", |
| 29 |
"#FB9A99", "#E31A1C", "#FDBF6F", "#FF7F00" ] |
| 30 |
|
| 31 |
colors.reverse() |
| 32 |
|
| 33 |
# for reference : ranges of the RRAs |
| 34 |
# base step size 60 sec |
| 35 |
# step 1 : 60 sec x 1600 points : 1600 min : 26,67 hr : 1.11 days |
| 36 |
# step 2 : 120 sec x 1200 points : 2400 min : 40 hr : 1,67 days |
| 37 |
# step 10 : 600 sec x 1800 points : 18 000 min : 300 hr : 12,5 days |
| 38 |
# step 30 : 1800 sec x 2500 points : 75 000 min : 1250 hr : 52.08 days |
| 39 |
# step 120 : 7200 sec x 1000 points : 120 000 min : 2000 hr : 83.33 days |
| 40 |
# step 480 : 28800 sec x 1000 points : 480 000 min : 8000 hr : 333.33 days |
| 41 |
# step 1440 : 86400 sec x 3650 points : 3650 days : 10 years |
| 42 |
|
| 43 |
# resolutions of RRAs |
| 44 |
|
| 45 |
# 1 : 60 sec : 1 min |
| 46 |
# 2 : 120 sec : 2 min |
| 47 |
# 3 : 600 sec : 10 min |
| 48 |
# 4 : 1 800 sec : 30 min |
| 49 |
# 5 : 7 200 sec : 120 min : 2 hr |
| 50 |
# 6 : 28 800 sec : 480 min : 8 hr |
| 51 |
# 7 : 86 400 sec : 1440 min : 24 hr : 1 day |
| 52 |
|
| 53 |
plotrangedef = { |
| 54 |
'hr' : { 'timeargs' : [ '-s', 'n-200min', '-e', 'n' ], |
| 55 |
'timetag' : 'hr', |
| 56 |
'avrange' : 24*3600, |
| 57 |
'avres' : 60, |
| 58 |
'sizeargs' : { 'small' : [ '--width', '200', '--height', '125', |
| 59 |
'--x-grid', |
| 60 |
'MINUTE:20:HOUR:1:HOUR:1:0:%H:00' |
| 61 |
], |
| 62 |
'large' : [ '--width', '800', '--height', '500' ] |
| 63 |
}, |
| 64 |
}, |
| 65 |
'day' : { 'timeargs' : [ '-s', 'n-2000min', '-e', 'n' ], |
| 66 |
'timetag' : 'day', |
| 67 |
'avrange' : 24*3600, |
| 68 |
'avres' : 60, |
| 69 |
'sizeargs' : { 'small' : [ '--width', '200', '--height', '125', |
| 70 |
'--x-grid', |
| 71 |
'HOUR:6:DAY:1:HOUR:12:0:%a %H:00' |
| 72 |
], |
| 73 |
'large' : [ '--width', '1000', '--height', '625' ] |
| 74 |
}, |
| 75 |
}, |
| 76 |
'week' : { 'timeargs' : [ '-s', 'n-288hr', '-e', 'n' ], |
| 77 |
'timetag' : 'week', |
| 78 |
'avrange' : 7*24*3600, |
| 79 |
'avres' : 600, |
| 80 |
'sizeargs' : { 'small' : [ '--width', '576', '--height', '125' ], |
| 81 |
'large' : [ '--width', '1728', '--height', '375', |
| 82 |
'-n', 'DEFAULT:16:'] |
| 83 |
}, |
| 84 |
}, |
| 85 |
|
| 86 |
# note the construction "repr(576*n)" here --- this is because the plot is |
| 87 |
# (a multiple of) 576 pixels, and 120 min is one of the RRAs, so choosing |
| 88 |
# a lower limit of 576*120 gives us a plot with one pixel per RRA bin. |
| 89 |
|
| 90 |
'month' : { 'timeargs' : [ '-s', 'n-'+repr(576*120)+'min', '-e', 'n'], |
| 91 |
'timetag' : 'month', |
| 92 |
'avrange' : 31*24*3600, |
| 93 |
'avres' : 1800, |
| 94 |
'sizeargs' : { 'small' : [ '--width', '576', '--height', '105'], |
| 95 |
'large' : [ '--width', '2304', '--height', '420', |
| 96 |
'-n', 'DEFAULT:18:', |
| 97 |
'--x-grid', |
| 98 |
'HOUR:12:DAY:1:DAY:3:86400:%d-%b' |
| 99 |
] |
| 100 |
}, |
| 101 |
}, |
| 102 |
|
| 103 |
'year' : { 'timeargs' : [ '-s', 'n-'+repr((576/2)*1440)+'min', '-e', 'n'], |
| 104 |
'timetag' : 'year', |
| 105 |
'avrange' : 365*24*3600, |
| 106 |
'avres' : 86400, |
| 107 |
'sizeargs' : { 'small' : [ '--width', '576', '--height', '105'], |
| 108 |
'large' : [ '--width', '2304', '--height', '420'] |
| 109 |
}, |
| 110 |
}, |
| 111 |
} |
| 112 |
|
| 113 |
commonargs = ['--imgformat', 'PNG', |
| 114 |
'--legend-position=east', '--legend-direction=bottomup'] |
| 115 |
|
| 116 |
import rrdtool |
| 117 |
import time |
| 118 |
import glob |
| 119 |
|
| 120 |
### function definitions |
| 121 |
|
| 122 |
def doplot(grouplist, dbtype, psize, timetag, sizeargs, timeargs, pcents): |
| 123 |
|
| 124 |
defs = list() |
| 125 |
plots = list() |
| 126 |
|
| 127 |
data_defs = list() |
| 128 |
plot_defs = list() |
| 129 |
|
| 130 |
for group in (grouplist + ['total']): |
| 131 |
data_defs.append('DEF:'+group+'='+DATADIR+group+'.'+dbtype+'.rrd:'+dbtype+':AVERAGE') |
| 132 |
|
| 133 |
for idx in range(len(grouplist)): |
| 134 |
group = grouplist[idx] |
| 135 |
pdefstr = 'AREA' ':' + group + colors[idx] + ':' + group |
| 136 |
if pcents: |
| 137 |
pdefstr = pdefstr + ' (' + "%4.1f" % (pcents[group]) + ')' |
| 138 |
pdefstr = pdefstr + '\\n' |
| 139 |
if idx > 0: |
| 140 |
pdefstr = pdefstr + ':STACK' |
| 141 |
plot_defs.append(pdefstr) |
| 142 |
|
| 143 |
plot_defs.append('LINE:total#000000:total') |
| 144 |
|
| 145 |
pargs = [ PLOTDIR + dbtype + '-' + timetag + '-' + psize + '.png'] + \ |
| 146 |
commonargs + ['-l', '0'] + sizeargs[psize] + timeargs + \ |
| 147 |
data_defs + plot_defs |
| 148 |
rrdtool.graph( *pargs ) |
| 149 |
|
| 150 |
def doplot_wait(grouplist, dbtype, psize, timetag, sizeargs, timeargs): |
| 151 |
|
| 152 |
defs = list() |
| 153 |
plots = list() |
| 154 |
|
| 155 |
data_defs = list() |
| 156 |
plot_defs = list() |
| 157 |
|
| 158 |
for group in (grouplist + ['rollover','lastroll']): |
| 159 |
data_defs.append('DEF:'+group+'='+DATADIR+group+'.'+dbtype+'.rrd:'+dbtype+':AVERAGE') |
| 160 |
|
| 161 |
for idx in range(len(grouplist)): |
| 162 |
group = grouplist[idx] |
| 163 |
pdefstr = 'LINE3' ':' + group + colors[idx] + ':' + group |
| 164 |
pdefstr = pdefstr + '\\n' |
| 165 |
plot_defs.append(pdefstr) |
| 166 |
|
| 167 |
plot_defs.append('LINE2:rollover#660198') |
| 168 |
plot_defs.append('LINE2:lastroll#000000') |
| 169 |
|
| 170 |
pargs = [ PLOTDIR + dbtype + '-' + timetag + '-' + psize + '.png'] + \ |
| 171 |
['--slope-mode', '-o'] + \ |
| 172 |
commonargs + sizeargs[psize] + timeargs + \ |
| 173 |
data_defs + plot_defs |
| 174 |
rrdtool.graph( *pargs ) |
| 175 |
|
| 176 |
def makeplots(prangedef): |
| 177 |
|
| 178 |
resolu = prangedef['avres'] |
| 179 |
|
| 180 |
# first need to find "top eight" list |
| 181 |
# base it on running jobs |
| 182 |
|
| 183 |
now=int(time.mktime(time.localtime())) |
| 184 |
end = (now / resolu) * resolu |
| 185 |
start = end - (prangedef['avrange']) + resolu |
| 186 |
|
| 187 |
### block finding 'top N' group list ### |
| 188 |
|
| 189 |
tgroup = dict() # structure tgroup[groupname] = total of hourly average |
| 190 |
|
| 191 |
running_files = glob.glob(DATADIR+'*.running.rrd') |
| 192 |
for db in running_files: |
| 193 |
group = db[len(DATADIR):db.find('.running.rrd')] |
| 194 |
tup = rrdtool.fetch(db,'AVERAGE','-r', repr(resolu), |
| 195 |
'-s', repr(start), '-e', repr(end)) |
| 196 |
vallist = [0] # start with zero, in case no vals returned, get zero as answer |
| 197 |
for tup2 in tup[2]: |
| 198 |
val = tup2[0] |
| 199 |
if val: |
| 200 |
vallist.append(val) |
| 201 |
if group == "total": |
| 202 |
totval = sum(vallist) |
| 203 |
else: |
| 204 |
tgroup[group] = sum(vallist) |
| 205 |
|
| 206 |
pgroup = dict() |
| 207 |
for g in tgroup.keys(): |
| 208 |
pgroup[g] = 100*tgroup[g]/totval |
| 209 |
|
| 210 |
groups_sorted = sorted(tgroup, key=tgroup.get, reverse=False) |
| 211 |
topgroups=groups_sorted[-NUMGROUPS:] |
| 212 |
|
| 213 |
if opts.rankonly: |
| 214 |
print "Ranks for", prangedef['timetag'], " resolution is", resolu |
| 215 |
for g in reversed(groups_sorted): |
| 216 |
if tgroup[g] > 0: |
| 217 |
print "%10s %12d" % (g, tgroup[g]) |
| 218 |
return |
| 219 |
|
| 220 |
### end block 'top N' group list ### |
| 221 |
|
| 222 |
### block generating plots ### |
| 223 |
|
| 224 |
|
| 225 |
for dbtype in ['queued', 'running', 'waittime']: |
| 226 |
|
| 227 |
### this is a bit of a hack : we only want pgroups for when it's |
| 228 |
### a 'running' database and we don't want it for timetag hour. |
| 229 |
### fix this up here |
| 230 |
|
| 231 |
if dbtype == 'running' and prangedef['timetag'] != 'hr': |
| 232 |
percents = pgroup |
| 233 |
else: |
| 234 |
percents = None |
| 235 |
for psize in ['small', 'large']: |
| 236 |
if dbtype == 'waittime': |
| 237 |
doplot_wait(topgroups, dbtype, psize, prangedef['timetag'], |
| 238 |
prangedef['sizeargs'], |
| 239 |
prangedef['timeargs'], |
| 240 |
) |
| 241 |
else: |
| 242 |
doplot(topgroups, dbtype, psize, prangedef['timetag'], |
| 243 |
prangedef['sizeargs'], |
| 244 |
prangedef['timeargs'], |
| 245 |
percents |
| 246 |
) |
| 247 |
|
| 248 |
for k in plotrangedef.keys(): |
| 249 |
makeplots(plotrangedef[k]) |
| 250 |
|
| 251 |
import sys |
| 252 |
sys.exit(0) |
Parent Directory
| 
Revision Log