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$state=='BOOT')])) x<-c(x,ts) n<-c(n,node_count) o<-c(o,online_count) } print(length(x)) print(length(n)) print(length(o)) return (rbind(x,n,o)) } lowess_smooth <- function (x, y, delta=(60*60*24), f=0.02) { a<-lowess(x, y, delta=delta, f=f) return (a); } ##### ns <- read.csv('node-status-jun09-feb10.csv', sep=',', header=TRUE) an <- available_nodes(ns, "2009-06-10", "2010-02-28", 'day') an_x<-an[1,][which(as.numeric(an[2,]) > 100)] an_y<-an[2,][which(as.numeric(an[2,]) > 100)] #### #fb7 <- read.csv('findbad_raw_2007.csv', sep=',', header=TRUE) #fb8 <- read.csv('findbad_raw_2008.csv', sep=',', header=TRUE) #fb9 <- read.csv('findbad_raw_2009.csv', sep=',', header=TRUE) z7<- online_nodes(fb7) z8<- online_nodes(fb8) z9<- online_nodes(fb9) zx <- c(z7[1,],z8[1,],z9[1,]) zy_reg <- c(z7[2,], z8[2,],z9[2,]) zy_avail <- c(z7[3,], z8[3,],z9[3,]) start_image("rt_aggregate_node_traffic.png") par(mfrow=c(2,1)) par(mai=c(0,1,0.1,0.1)) a_reg<-lowess_smooth(zx, zy_reg) plot(a_reg$x, a_reg$y, ylim=c(0,700), xlim=c(min(x1), max(x1)), type='l', pch='.', axes=F, ylab="Online Node Count", xlab="") sx <- zx[which(zy_avail > 330)] sy <- zy_avail[which(zy_avail > 330)] sx <- c(sx[1:2037],sx[2061:length(sx)]) sy <- c(sy[1:2037],sy[2061:length(sy)]) sx <- c(sx[1:1699],sx[1701:1707],sx[1709:length(sx)]) sy <- c(sy[1:1699],sy[1701:1707],sy[1709:length(sy)]) lines(sx, sy, col='grey80', pch='.') lines(an_x, an_y, col='grey80', pch='.') a_avail<-lowess_smooth(zx, zy_avail) lines(a_avail$x, a_avail$y, col='red', pch='.') a_avail_m3<-lowess_smooth(an_x, an_y) lines(a_avail_m3$x, a_avail_m3$y, col='red', pch='.') axis(2, las=1) x_online_node_list <- c(tstamp("2004-6-1"), tstamp("2005-6-1"), tstamp("2006-6-1"), tstamp("2007-11-1")) y_online_node_list <- c(330, 480, 500, 550) lines(x_online_node_list, y_online_node_list, col='grey80') #abline_at_date('2005-01-01', 'grey60') #abline_at_date('2006-01-01', 'grey60') #abline_at_date('2007-01-01', 'grey60') #abline_at_date('2008-01-01', 'grey60') #abline_at_date('2009-01-01', 'grey60') #abline_at_date('2010-01-01', 'grey60') tstamp_20041201 <-abline_at_date("2004-12-01", col='grey60', lty=2) tstamp_20050301 <-abline_at_date("2005-03-01", col='grey60', lty=2) tstamp_20050701 <-abline_at_date("2005-07-01", col='grey60', lty=2) tstamp_20051101 <-abline_at_date("2005-11-01", col='grey60', lty=2) tstamp_20051201 <-abline_at_date("2005-12-01", col='grey60', lty=2) tstamp_20070101 <-abline_at_date("2007-01-01", col='grey60', lty=2) tstamp_20070501 <-abline_at_date("2007-05-01", col='grey60', lty=2) tstamp_20080601 <-abline_at_date("2008-06-01", col='grey60', lty=2) tstamp_20080815 <-abline_at_date("2008-08-15", col='grey60', lty=2) tstamp_20090501 <-abline_at_date("2009-05-01", col='grey60', lty=2) tstamp_20100201 <-abline_at_date("2010-02-01", col='white', lty=2) text(x=c( tstamp_20041201+(tstamp_20050301-tstamp_20041201)/2, tstamp_20050301+(tstamp_20050701-tstamp_20050301)/2, tstamp_20050701+(tstamp_20051101-tstamp_20050701)/2, tstamp_20051201+(tstamp_20070101-tstamp_20051201)/2, tstamp_20070101+(tstamp_20070501-tstamp_20070101)/2, tstamp_20080601+(tstamp_20080815-tstamp_20080601)/2, tstamp_20090501+(tstamp_20100201-tstamp_20090501)/2 ), y=c(700), labels=c('3.0', '3.1', '3.1S', '3.2', '4.0', '4.2', '4.3')) par(mai=c(1,1,0.1,0.1)) # system("parse_rt_data.py 3 > rt_data.csv"); t <- read.csv('rt_data_2004-2010.csv', sep=',', header=TRUE) t2 <- t[which(t$complete == 1),] ot <- open_tickets(t2, '2004/1/1', '2010/2/28', 'day', "%b") 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", xlab="Date") # , ylim=c(0,260)) lines(a_ot$x, round(a_ot$y), col='red') 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') end_image() m <- read.csv('rt_monitor_data.csv', sep=',', header=TRUE) m2 <- m[which(m$complete == 1),] otm <- open_tickets(m2, '2004/1/1', '2010/2/28', 'day', "%b") xm<-as.numeric(otm[1,]) ym<-as.numeric(otm[2,]) a<-lowess(xm, ym, delta=(60*60*24), f=0.02) x<-a$x y<-a$y lines(x, round(y), col='blue') #end_image() #t_july08 <-unclass(as.POSIXct("2008-07-01", origin="1970-01-01"))[1] #breaks <- unique(fb8$timestamp[which(fb8$timestamp < t_july08)]) #fb8_boot <- fb8$timestamp[which(fb8$state=="BOOT" & fb8$timestamp < t_july08)] #h8<-hist(fb8_boot, breaks=breaks[which(!is.na(breaks) & breaks!=0)]) # #breaks <- unique(as.numeric(as.character(fb9$timestamp))) #fb9_boot <- as.numeric(as.character(fb9$timestamp[which(fb9$state=="BOOT")])) #hist(fb9_boot, breaks=breaks[which(!is.na(breaks) & breaks >= 1230775020)])