5 nsh <- read.csv('node_status_history.csv', sep=',', header=TRUE)
7 # system("./harvest_nodehistory.py > node_status_history_nopcu.csv")
8 nsh_nopcu <- read.csv('node_status_history_nopcu.csv', sep=',', header=TRUE)
10 nsh_m1 <- read.csv('node_status_history_m1.csv', sep=',', header=TRUE)
11 # system("stats-m1/harvest_nodehistory_m1.py > ./node_status_history_m1_nopcu.csv")
12 nsh_m1_nopcu_total <- read.csv('node_status_history_m1_nopcu_total.csv', sep=',', header=TRUE)
13 nsh_m1_nopcu_notice <- read.csv('node_status_history_m1_nopcu.csv', sep=',', header=TRUE)
14 nsh_m1_nopcu_kernel <- read.csv('node_status_history_m1_nopcu_may08sep08.csv', sep=',', header=TRUE)
15 nsh_m1_pcu <- read.csv('node_status_history_m1_pcu.csv', sep=',', header=TRUE)
18 node_hist_image <- function (t, year, from, to, max=0, type="week", title="")
20 dates <-seq(as.Date(from), as.Date(to), type)
21 months <- format(dates, "%b-%d")
22 hbreaks<-unclass(as.POSIXct(dates))
24 image <- matrix(data=0, nrow=max(as.numeric(t$hostname)), ncol=length(hbreaks))
26 for ( i in seq(1, length(hbreaks)) )
28 # find the range : d plus a day
31 # find unique hosts in this day range
32 t_sub <- t[which(t$start > d & t$start <= d_end & t$status == 'down'),]
33 unique_hosts <- unique(t_sub$hostname)
34 if (length(unique_hosts) == 0 ) { next }
36 host_n_list <- unique_hosts
37 host_s_list <- as.character(unique_hosts)
39 for ( hi in seq(1, length(unique_hosts)) )
41 host_s <- host_s_list[hi]
42 host_n <- host_n_list[hi]
43 # events for this host after d (to avoid already identified events)
44 ev <- t[which(t$hostname == host_s & t$start > d ),]
45 print (sprintf("events length for host %s %s", host_s, length(ev$start)));
46 # get down events for this host
47 down_ev_index_list <- which(ev$status == 'down')
48 for ( e_i in down_ev_index_list )
50 if ( e_i == length(ev$status) ) {
51 # then the node ends down, so fill in the rest with 1.
52 for ( j in seq(i,length(hbreaks)) ) {
56 # then there is a subsequent 'good' event
59 dbreaks <- seq(d,good_ev$start+60*60*24,60*60*24)
60 # for every index for time d, to good_ev$start
62 print (sprintf("length %s",l));
63 for ( j in seq(i,i+l) )
71 myImagePlot(image, xLabels=months, yLabels=c(""), title=title)
77 node_hist_dist <- function (t, year, from, to, max=0, type="week", title="")
79 dates <-seq(as.Date(from), as.Date(to), type)
80 months <- format(dates, "%b-%d")
81 hbreaks<-unclass(as.POSIXct(dates))
82 current_ts <- unclass(as.POSIXct(Sys.Date()))
86 unique_hosts <- unique(t$hostname)
87 host_n_list <- unique_hosts
88 host_s_list <- as.character(unique_hosts)
92 for ( hi in seq(1, length(unique_hosts)) )
94 host_s <- host_s_list[hi]
95 host_n <- host_n_list[hi]
96 # events for this host after d (to avoid already identified events)
97 ev <- t[which( t$hostname == host_s ),]
98 print (sprintf("events length for host %s %s", host_s, length(ev$start)));
99 # get down events for this host
100 down_ev_index_list <- which(ev$status == 'down')
101 for ( e_i in down_ev_index_list )
103 # when equal, there is no resolution so leave it as down
104 if ( e_i != length(ev$status) ) {
105 good_ev <- ev[e_i+1,]
107 dist <- c(dist, good_ev$start - down_ev$start)
108 } else if ( e_i == length(ev$status) && length(ev$status) == 1) {
109 print (sprintf("DOWN FOREVER! %s", length(ev$start) ))
111 dist <- c(dist, 10*current_ts - ev$start)
121 # data collected from M2 pickle files
122 dnc <- read.csv('daily-available-node-count.csv', sep=',', header=TRUE)
124 dnc2<-add_timestamp(dnc)
126 tstamp_08 <-unclass(as.POSIXct("2008-05-07", origin="1970-01-01"))[1]
127 dnc2 <- dnc2[which( dnc2$start > tstamp_08 ),]
130 dates <-seq(as.Date('2008-05-07'), as.Date('2009-05-07'), 'week')
131 months <- format(dates, "%b")
132 hbreaks<-unclass(as.POSIXct(dates))
134 x_start<-unclass(as.POSIXct("2008-05-01", origin="1970-01-01"))[1]
135 x_end <-unclass(as.POSIXct("2009-06-1", origin="1970-01-01"))[1]
137 print ("fuckyou 0b");
139 tstamp_0510 <-abline_at_date("2008-05-10", col='grey20', lty=0, height=570)
140 # dates takes from reboot_image() output for API events.
142 tstamp_0610 <-abline_at_date("2008-06-10", col='grey40', lty=5, height=570)
143 tstamp_0815 <-abline_at_date("2008-08-15", col='grey70', lty=1, height=570)
146 #tstamp_0905 <-abline_at_date("2008-09-05", col='grey70', height=570)
147 tstamp_0924 <-abline_at_date("2008-09-24", col='grey70', lty=1, height=570)
148 tstamp_1015 <-abline_at_date("2008-10-15", col='grey40', lty=5, height=570)
150 #tstamp_1105 <-abline_at_date("2008-11-05", col='white', lty=2, height=570)
151 #tstamp_1214 <-abline_at_date("2008-12-14", col='grey70', height=570)
152 tstamp_0223 <-abline_at_date("2009-02-23", col='grey70', height=570)
154 #tstamp_0313 <-abline_at_date("2009-03-13", col='grey70', height=570)
156 print ("fuckyou 0c");
157 start_image("myops_restore_nopcu.eps")
159 par(mai=c(.9,.8,.1,.1))
161 plot(dnc2$start[which(!is.na(dnc2$available) & (dnc2$start > tstamp_0815 & dnc2$start <= tstamp_1015) )],
162 dnc2$available[which(!is.na(dnc2$available) & (dnc2$start > tstamp_0815 & dnc2$start <= tstamp_1015) )],
163 type='l', col='red', ylim=c(0,600), xlim=c(x_start, x_end),
164 xlab="", ylab="a) Online Node Count", axes=F)
167 lines(dnc2$start[which(!is.na(dnc2$available) & (dnc2$start > tstamp_0223) )],
168 dnc2$available[which(!is.na(dnc2$available) & (dnc2$start > tstamp_0223) )],
171 lines(dnc2$start[which(!is.na(dnc2$available) & dnc2$start > tstamp_1015 & dnc2$start <= tstamp_0223)], dnc2$available[which(!is.na(dnc2$available)& dnc2$start > tstamp_1015 & dnc2$start <= tstamp_0223)], lty=2, type='l', col='blue')
175 lines(dnc2$start[which(!is.na(dnc2$available) & dnc2$start > tstamp_0510 & dnc2$start <= tstamp_0815)], dnc2$available[which(!is.na(dnc2$available)& dnc2$start > tstamp_0510 & dnc2$start <= tstamp_0815)], lty=3, type='l', col='darkgreen')
177 #lines(dnc2$start[which(!is.na(dnc2$available))], dnc2$available[which(!is.na(dnc2$available))],
178 #type='l', col='red', ylim=c(0,1000))
180 axis(1, cex.axis=0.7, labels=months, at=hbreaks)
184 tstamp_0510 <-abline_at_date("2008-05-10", col='grey20', lty=0, height=570)
185 # dates takes from reboot_image() output for API events.
187 tstamp_0610 <-abline_at_date("2008-06-10", col='grey40', lty=5, height=570)
188 tstamp_0815 <-abline_at_date("2008-08-15", col='grey70', lty=1, height=570)
191 #tstamp_0905 <-abline_at_date("2008-09-05", col='grey70', height=570)
192 tstamp_0924 <-abline_at_date("2008-09-24", col='grey70', lty=1, height=570)
193 tstamp_1015 <-abline_at_date("2008-10-15", col='grey40', lty=5, height=570)
195 #tstamp_1105 <-abline_at_date("2008-11-05", col='white', lty=2, height=570)
196 #tstamp_1214 <-abline_at_date("2008-12-14", col='grey70', height=570)
197 tstamp_0223 <-abline_at_date("2009-02-23", col='grey70', height=570)
199 #tstamp_0313 <-abline_at_date("2009-03-13", col='grey70', height=570)
201 #text(x=c(tstamp_0610+(tstamp_0815-tstamp_0610)/2,
202 # tstamp_0815+(tstamp_0905-tstamp_0815)/2,
203 # tstamp_0924+(tstamp_1015-tstamp_0924)/2,
204 # tstamp_1015+(tstamp_1214-tstamp_1015)/2,
205 # tstamp_1214+(tstamp_0223-tstamp_1214)/2,
206 # tstamp_0223+(tstamp_0313-tstamp_0223)/2),
208 # labels=c("bug1", 'fix1', 'fix2', 'fix3', 'bug2', 'fix4')) #, 'fix 2', 'fix 3', 'fix 4'))
210 text(x=c( tstamp_0815,
215 labels=c('fix1', 'fix2', 'fix3'))
218 text(x=c(tstamp_0510-(60*60*24*10),
223 labels=c('Events:', 'bug1', 'bug2'))
225 mtext("2008 2009", 1,2)
226 legend(unclass(as.POSIXct("2009-02-23", origin="1970-01-01"))[1], 200,
228 legend=c("Typical MyOps", "Bug1", "Bug2", 'Bug Added', 'Fix Added'),
229 pch=c('-', '-', '-'),
230 col=c('red', 'darkgreen', 'blue', 'grey20', 'grey70'),
231 lty=c(1, 3, 2, 5, 1), merge=T)
233 #legend=c("Registered", "Online", 'Kernel Update', 'MyOps Event'),
234 #pch=c('-', '-', '-', '-'),
235 #col=c('blue', 'red', 'grey20', 'grey70'),
236 #lty=c(1, 1, 2, 1), merge=T)
238 ###################################
240 t_0815 <- unclass(as.POSIXct("2008-08-15", origin="1970-01-01"))[1]
241 t_0905 <- unclass(as.POSIXct("2008-09-05", origin="1970-01-01"))[1]
243 t_0924 <- unclass(as.POSIXct("2008-09-24", origin="1970-01-01"))[1]
244 t_1015 <- unclass(as.POSIXct("2008-10-15", origin="1970-01-01"))[1]
246 t_0223 <- unclass(as.POSIXct("2009-02-23", origin="1970-01-01"))[1]
247 t_0313 <- unclass(as.POSIXct("2009-03-13", origin="1970-01-01"))[1]
249 nsh_m1_short <- nsh_m1_nopcu_total[which(
250 (nsh_m1_nopcu_total$start > t_0815 & nsh_m1_nopcu_total$start <= t_0313) ),]
251 nsh_dist_m1 <- node_hist_dist(nsh_m1_short, '2008', '2008-05-01', '2009-05-22', 0, 'day')
252 d_m1_total<- ecdf(nsh_dist_m1/(60*60*24))
254 # NOTE: something happened betweeen 10-2 and 10-3
256 t_1015 <- unclass(as.POSIXct("2008-10-15", origin="1970-01-01"))[1]
257 t_0224 <- unclass(as.POSIXct("2009-02-24", origin="1970-01-01"))[1]
258 nsh_m1_short <- nsh_m1_nopcu_notice[which(nsh_m1_nopcu_notice$start > t_1015 & nsh_m1_nopcu_notice$start <= t_0224),]
259 nsh_dist_m1 <- node_hist_dist(nsh_m1_short, '2008', '2008-10-01', '2009-03-22', 0, 'day')
260 d_m1_notice_bug <- ecdf(nsh_dist_m1/(60*60*24))
264 t_0530 <- unclass(as.POSIXct("2008-05-30", origin="1970-01-01"))[1]
265 t_0815 <- unclass(as.POSIXct("2008-08-15", origin="1970-01-01"))[1]
266 nsh_m1_short <- nsh_m1_nopcu_kernel[which(nsh_m1_nopcu_kernel$start > t_0530 & nsh_m1_nopcu_kernel$start <= t_0815),]
267 nsh_dist_m1 <- node_hist_dist(nsh_m1_short, '2008', '2008-05-10', '2008-08-15', 0, 'day')
268 d_m1_kernel_bug <- ecdf(nsh_dist_m1/(60*60*24))
271 nsh_m1_short <- nsh_m1_pcu[which(nsh_m1_pcu$start > t_0815 & nsh_m1_pcu$start <= t_0224),]
272 nsh_dist_m1 <- node_hist_dist(nsh_m1_short, '2008', '2008-05-10', '2009-03-22', 0, 'day')
273 d_m1_pcu <- ecdf(nsh_dist_m1/(60*60*24))
277 # d<-ecdf(nsh_dist[which(nsh_dist/(60*60*24) < 90 )]/(60*60*24)),
279 par(mai=c(.9,.9,.1,.3))
280 #plot(d, xlim=c(0,180), ylim=c(0,1), axes=F, xlab="Days to Resolve", ylab="Percentile",
281 # col.hor='red', col.vert='red', pch='.', col.points='red', main="")
285 print ("fuckyou 4a");
286 plot(d_m1_total, xlim=c(0,x_lim_max), ylim=c(0,1), axes=F, xlab="Days to Resolve",
287 ylab="b) Fraction of Offline Nodes Restored", col.hor='red', col.vert='red', pch='.',
288 col.points='red', main="")
291 plot(d_m1_notice_bug, xlim=c(0,x_lim_max), ylim=c(0,1), xlab="Days to Resolve",
292 col.hor='blue', col.vert='blue', pch='.',
293 col.points='blue', lty=2, add=TRUE)
296 plot(d_m1_kernel_bug, xlim=c(0,x_lim_max), ylim=c(0,1), xlab="Days to Resolve",
297 col.hor='darkgreen', col.vert='darkgreen', pch='.',
298 col.points='darkgreen', lty=3, add=TRUE)
300 #plot(d_m1_pcu, xlim=c(0,x_lim_max), ylim=c(0,1), xlab="Days to Resolve",
301 # col.hor='purple', col.vert='purple', pch='.',
302 # col.points='purple', lty=4, add=TRUE)
304 weeks <- c(0,7,14,21,28,60,90,120,150,180)
305 axis(1, labels=weeks, at=weeks)
306 percentages <- c(0,0.25, 0.5, 0.75, 0.85, 0.95, 1)
307 axis(2, las=1, labels=percentages, at=percentages)
309 abline(v=c(7,14,21,28), col='grey80', lty=2)
310 abline(h=c(0.5, 0.6, 0.75, 0.85, 0.95 ), col='grey80', lty=2)
311 abline(v=c(91), col='grey80', lty=2)
316 legend=c("Typical MyOps", "Only Notices", "No Notices"),
317 pch=c('-', '-', '-'),
318 col=c('red', 'blue', 'darkgreen'),
319 lty=c(1, 2, 3), merge=T)