source("functions.r"); available_nodes <- function (ns, from, to, type, fmt="%b") { # find 'type' range of days dates <-seq(as.Date(from), as.Date(to), type) months <- format(dates, fmt) hbreaks<-unclass(as.POSIXct(dates)) xx<-NULL; yy<-NULL; for ( i in seq(1,length(hbreaks)-1) ) { # get range from ns ns_sub <- ns[which(ns$date > hbreaks[i] & ns$date <= hbreaks[i+1] & ns$status == 'BOOT'),] nodes <- length(ns_sub$date) xx<- c(xx, hbreaks[i]) yy<- c(yy, nodes) } m<- months[1:length(months)-1] return (rbind(xx,yy,m)) } open_tickets <- function (t, from, to, type, fmt="%b") { # find 'type' range of days dates <-seq(as.Date(from), as.Date(to), type) months <- format(dates, fmt) hbreaks<-unclass(as.POSIXct(dates)) xx<-NULL; yy<-NULL; for ( i in seq(1,length(hbreaks)-1) ) { # identify any tickets with a start time in range, lastreply in range # or where both start is less and lastreply is greater than the range t_sub <- t[which( (t$start < hbreaks[i] & t$lastreply > hbreaks[i+1]) | (t$start > hbreaks[i] & t$start <= hbreaks[i+1]) | (t$lastreply > hbreaks[i] & t$lastreply <= hbreaks[i+1]) ),] tickets <- length(t_sub$start) #if ( nrow(t_sub) > 0 ){ # for ( j in seq(1,nrow(t_sub)) ) # { # #print(sprintf("id %s, date %s", t_sub[i,'ticket_id'], t_sub[i,'s1'])) # print(sprintf("id %s, date %s", t_sub[j,]$ticket_id, t_sub[j, 's1'])) # } #} xx<- c(xx, hbreaks[i]) yy<- c(yy, tickets) } m<- months[1:length(months)-1] return (rbind(xx,yy,m)) } online_nodes <- function (fb) { breaks <- unique(fb$timestamp) n<-NULL o<-NULL x<-NULL for (i in seq(1,length(breaks)) ) { ts <- breaks[i] sub <- fb[which(fb$timestamp == ts),] node_count <- length(unique(sub$hostname)) online_count <- length(unique(sub$hostname[which(sub$state=='BOOT')])) x<-c(x,ts) n<-c(n,node_count) o<-c(o,online_count) } print(length(x)) print(length(n)) print(length(o)) return (rbind(x,n,o)) } lowess_smooth <- function (x, y, delta=(60*60*24), f=0.02) { a<-lowess(x, y, delta=delta, f=f) return (a); } ##### # system("parse_rt_data.py 3 > rt_data.csv"); t <- read.csv('rt_data_2004-2010.csv', sep=',', header=TRUE) t2 <- t[which(t$complete == 1),] ot <- open_tickets(t2, '2004/1/1', '2010/2/28', 'day', "%b") start_image("rt_operator_overhead.png") par(mfrow=c(2,1)) par(mai=c(0,1,0.1,0.1)) x1<-as.numeric(ot[1,]) y1<-as.numeric(ot[2,]) a_ot<-lowess_smooth(x1, y1) plot(x1, y1, col='grey80', type='l', axes=F, ylab="Open Tickets (tickets/day)", xlab="Date", ylim=c(0,120)) # , ylim=c(0,260)) lines(a_ot$x, round(a_ot$y), col='black') #axis(1, labels=ot[3,], at=ot[1,], cex.axis=0.7) axis(2, las=1) #mtext("2004 2005 2006 2007 2008 2009", 1,2) #abline_at_date('2005-01-01', 'grey60') #abline_at_date('2006-01-01', 'grey60') #abline_at_date('2007-01-01', 'grey60') #abline_at_date('2008-01-01', 'grey60') #abline_at_date('2009-01-01', 'grey60') #abline_at_date('2010-01-01', 'grey60') abline(h=25, lty=2, col='grey80') abline(h=40, lty=2, col='grey80') tstamp_20041112 <-abline_at_date("2004-11-12", col='grey60', lty=2) tstamp_20050301 <-abline_at_date("2005-03-01", col='grey60', lty=2) tstamp_20050615 <-abline_at_date("2005-06-15", col='grey60', lty=2) tstamp_20051023 <-abline_at_date("2005-10-23", col='grey60', lty=2) tstamp_20070101 <-abline_at_date("2007-01-01", col='grey60', lty=2) tstamp_20070501 <-abline_at_date("2007-05-01", col='grey60', lty=2) tstamp_20080601 <-abline_at_date("2008-06-01", col='grey60', lty=2) tstamp_20080815 <-abline_at_date("2008-08-15", col='grey60', lty=2) tstamp_20090501 <-abline_at_date("2009-05-01", col='grey60', lty=2) tstamp_20100201 <-abline_at_date("2010-02-01", col='white', lty=2) text(x=c( tstamp_20041112+(tstamp_20050301-tstamp_20041112)/2, tstamp_20050301+(tstamp_20050615-tstamp_20050301)/2, tstamp_20050615+(tstamp_20051023-tstamp_20050615)/2, tstamp_20051023+(tstamp_20070101-tstamp_20051023)/2, tstamp_20070101+(tstamp_20070501-tstamp_20070101)/2, tstamp_20080601+(tstamp_20080815-tstamp_20080601)/2, tstamp_20090501+(tstamp_20100201-tstamp_20090501)/2 ), y=c(120), labels=c('3.0', '3.1', '3.1S', '3.2', '4.0', '4.2', '4.3')) par(mai=c(1,1,0.1,0.1)) for ( s in c(7) ) { d<- median_time_to_resolve_window(t2, "2004/1/1", "2010/2/28", s, "%b") plot(d[,1], exp(as.numeric(d[,5]))/24, type='l', lty=1, xlab="", axes=F, ylim=c(0.01, 15), ylab="Resolution Time by", col='grey50', xlim=c(min(x1), max(x1))) mtext("Quartile (days)", 2, 2) lines(d[,1], exp(as.numeric(d[,4]))/24, lty=1, col='black') lines(d[,1], exp(as.numeric(d[,3]))/24, lty=1, col='grey50') #axis(1, labels=d[,7], at=d[,1]) axis(1, labels=ot[3,], at=ot[1,], cex.axis=0.7) mtext("2004 2005 2006 2007 2008 2009", 1,2) axis(2, las=1) m<-round(max(exp(as.numeric(d[,4]))/24), 2) axis(2, labels=m, at=m, las=1) abline(h=m, lty=2, col='grey40') } tstamp_20041112 <-abline_at_date("2004-11-12", col='grey60', lty=2) tstamp_20050301 <-abline_at_date("2005-03-01", col='grey60', lty=2) tstamp_20050615 <-abline_at_date("2005-06-15", col='grey60', lty=2) tstamp_20051023 <-abline_at_date("2005-10-23", col='grey60', lty=2) tstamp_20070101 <-abline_at_date("2007-01-01", col='grey60', lty=2) tstamp_20070501 <-abline_at_date("2007-05-01", col='grey60', lty=2) tstamp_20080601 <-abline_at_date("2008-06-01", col='grey60', lty=2) tstamp_20080815 <-abline_at_date("2008-08-15", col='grey60', lty=2) tstamp_20090501 <-abline_at_date("2009-05-01", col='grey60', lty=2) tstamp_20100201 <-abline_at_date("2010-02-01", col='white', lty=2) text(x=c( tstamp_20041112+(tstamp_20050301-tstamp_20041112)/2, tstamp_20050301+(tstamp_20050615-tstamp_20050301)/2, tstamp_20050615+(tstamp_20051023-tstamp_20050615)/2, tstamp_20051023+(tstamp_20070101-tstamp_20051023)/2, tstamp_20070101+(tstamp_20070501-tstamp_20070101)/2, tstamp_20080601+(tstamp_20080815-tstamp_20080601)/2, tstamp_20090501+(tstamp_20100201-tstamp_20090501)/2 ), y=c(15), labels=c('3.0', '3.1', '3.1S', '3.2', '4.0', '4.2', '4.3')) end_image()