Commit f4576dca authored by Peter van 't Hof's avatar Peter van 't Hof

Merge branch 'feature_runplot' into 'develop'

Feature runplot

for solving issue #17

See merge request !56
parents e69b6f0c 036afba6
library(gsalib)
library(grid)
library(ggplot2)
library(gplots)
library(tools)
library(reshape)
library(plyr)
# Modified version, loading `grid` manually. Ggplot2 doesn't load this
#
# Standard command line switch. Can we loaded interactively for development
# or executed with RScript
#
args = commandArgs(TRUE)
onCMDLine = ! is.na(args[1])
if ( onCMDLine ) {
inputFileName = args[1]
outputPDF = args[2]
} else {
inputFileName = "~/workspaces/scratch/SingleSample_VQSRwNewSOR.jobreport.txt"
#inputFileName = "/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/Q-25718@node1149.jobreport.txt"
#inputFileName = "/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/rodPerformanceGoals/history/report.082711.txt"
outputPDF = NA
}
RUNTIME_UNITS = "(hours)"
ORIGINAL_UNITS_TO_RUNTIME_UNITS = 1/1000/60/60
#
# Helper function to aggregate all of the jobs in the report across all tables
#
allJobsFromReport <- function(report) {
names <- c("jobName", "startTime", "analysisName", "doneTime", "exechosts", "runtime")
sub <- lapply(report, function(table) table[,names])
do.call("rbind", sub)
}
#
# Creates segmentation plots of time (x) vs. job (y) with segments for the duration of the job
#
plotJobsGantt <- function(gatkReport, sortOverall, title, includeText) {
allJobs = allJobsFromReport(gatkReport)
if ( sortOverall ) {
allJobs = allJobs[order(allJobs$analysisName, allJobs$startTime, decreasing=T), ]
} else {
allJobs = allJobs[order(allJobs$startTime, decreasing=T), ]
}
allJobs$index = 1:nrow(allJobs)
minTime = min(allJobs$startTime)
allJobs$relStartTime = allJobs$startTime - minTime
allJobs$relDoneTime = allJobs$doneTime - minTime
allJobs$ganttName = paste(allJobs$jobName, "@", allJobs$exechosts)
maxRelTime = max(allJobs$relDoneTime)
p <- ggplot(data=allJobs, aes(x=relStartTime, y=index, color=analysisName))
p <- p + theme_bw()
p <- p + geom_segment(aes(xend=relDoneTime, yend=index), size=1, arrow=arrow(length = unit(0.1, "cm")))
if ( includeText )
p <- p + geom_text(aes(x=relStartTime, label=ganttName, hjust=0, vjust=-1), size=2)
p <- p + xlim(0, maxRelTime * 1.3)
p <- p + xlab(paste("Start time, relative to first job", RUNTIME_UNITS))
p <- p + ylab("Job number")
p <- p + ggtitle(title)
print(p)
}
#
# Plots scheduling efficiency at job events
#
plotProgressByTime <- function(gatkReport) {
allJobs = allJobsFromReport(gatkReport)
nJobs = dim(allJobs)[1]
allJobs = allJobs[order(allJobs$startTime, decreasing=F),]
allJobs$index = 1:nrow(allJobs)
minTime = min(allJobs$startTime)
allJobs$relStartTime = allJobs$startTime - minTime
allJobs$relDoneTime = allJobs$doneTime - minTime
times = sort(c(allJobs$relStartTime, allJobs$relDoneTime))
countJobs <- function(p) {
s = allJobs$relStartTime
e = allJobs$relDoneTime
x = c() # I wish I knew how to make this work with apply
for ( time in times )
x = c(x, sum(p(s, e, time)))
x
}
pending = countJobs(function(s, e, t) s > t)
done = countJobs(function(s, e, t) e < t)
running = nJobs - pending - done
d = data.frame(times=times, pending=pending, running=running, done=done)
p <- ggplot(data=melt(d, id.vars=c("times")), aes(x=times, y=value, color=variable))
p <- p + facet_grid(variable ~ ., scales="free")
p <- p + geom_line(size=2)
p <- p + xlab(paste("Time since start of first job", RUNTIME_UNITS))
p <- p + ggtitle("Job scheduling")
print(p)
}
#
# Creates tables for each job in this group
#
standardColumns = c("jobName", "startTime", "formattedStartTime", "analysisName", "intermediate", "exechosts", "formattedDoneTime", "doneTime", "runtime")
plotGroup <- function(groupTable) {
name = unique(groupTable$analysisName)[1]
groupAnnotations = setdiff(names(groupTable), standardColumns)
sub = groupTable[,c("jobName", groupAnnotations, "runtime")]
sub = sub[order(sub$iteration, sub$jobName, decreasing=F), ]
# create a table showing each job and all annotations
textplot(sub, show.rownames=F)
title(paste("Job summary for", name, "full itemization"), cex=3)
# create the table for each combination of values in the group, listing iterations in the columns
sum = cast(melt(sub, id.vars=groupAnnotations, measure.vars=c("runtime")), ... ~ iteration, fun.aggregate=mean)
textplot(as.data.frame(sum), show.rownames=F)
title(paste("Job summary for", name, "itemizing each iteration"), cex=3)
# histogram of job times by groupAnnotations
if ( length(groupAnnotations) == 1 && dim(sub)[1] > 1 ) {
# todo -- how do we group by annotations?
p <- ggplot(data=sub, aes(x=runtime)) + geom_histogram()
p <- p + xlab(paste("runtime", RUNTIME_UNITS)) + ylab("No. of jobs")
p <- p + ggtitle(paste("Job runtime histogram for", name))
print(p)
}
# as above, but averaging over all iterations
groupAnnotationsNoIteration = setdiff(groupAnnotations, "iteration")
if ( dim(sub)[1] > 1 ) {
try({ # need a try here because we will fail to reduce when there's just a single iteration
sum = cast(melt(sub, id.vars=groupAnnotationsNoIteration, measure.vars=c("runtime")), ... ~ ., fun.aggregate=c(mean, sd))
textplot(as.data.frame(sum), show.rownames=F)
title(paste("Job summary for", name, "averaging over all iterations"), cex=3)
}, silent=T)
}
}
# print out some useful basic information
print("Report")
print(paste("Project :", inputFileName))
convertUnits <- function(gatkReportData) {
convertGroup <- function(g) {
g$runtime = g$runtime * ORIGINAL_UNITS_TO_RUNTIME_UNITS
g$startTime = g$startTime * ORIGINAL_UNITS_TO_RUNTIME_UNITS
g$doneTime = g$doneTime * ORIGINAL_UNITS_TO_RUNTIME_UNITS
g
}
lapply(gatkReportData, convertGroup)
}
#
# Plots runtimes by analysis name and exechosts
#
# Useful to understand the performance of analysis jobs by hosts,
# and to debug problematic nodes
#
plotTimeByHost <- function(gatkReportData) {
fields = c("analysisName", "exechosts", "runtime")
runtimes = data.frame()
for ( report in gatkReportData ) {
runtimes = rbind(runtimes, report[,fields])
}
plotMe <- function(name, vis) {
p = ggplot(data=runtimes, aes(x=exechosts, y=runtime, group=exechosts, color=exechosts))
p = p + facet_grid(analysisName ~ ., scale="free")
p = p + vis()
p = p + xlab("Job execution host")
p = p + ggtitle(paste(name, "of job runtimes by analysis name and execution host"))
p = p + ylab(paste("Distribution of runtimes", RUNTIME_UNITS))
p = p + theme(axis.text.x=element_text(angle=45, hjust=1, vjust=1))
print(p)
}
plotMe("Boxplot", geom_boxplot)
plotMe("Jittered points", geom_jitter)
}
mergeScattersForAnalysis <- function(table) {
#allJobs$ganttName = paste(allJobs$jobName, "@", allJobs$exechosts)
ddply(table, .(analysisName, iteration), summarize,
jobName = analysisName[1],
exechosts = paste(length(exechosts), "hosts"),
formattedStartTime = "NA",
formattedDoneTime = "NA",
intermediate = intermediate[1],
startTime = min(startTime),
doneTime = min(startTime) + sum(runtime),
runtime = sum(runtime))
}
mergeScatters <- function(report) {
newReport = list()
for ( name in names(gatkReportData) ) {
newReport[[name]] = mergeScattersForAnalysis(gatkReportData[[name]])
}
newReport
}
# read the table
gatkReportData <- gsa.read.gatkreport(inputFileName)
gatkReportData <- convertUnits(gatkReportData)
#print(summary(gatkReportData))
if ( ! is.na(outputPDF) ) {
pdf(outputPDF, height=8.5, width=11)
}
plotJobsGantt(gatkReportData, T, "All jobs, by analysis, by start time", F)
plotJobsGantt(gatkReportData, F, "All jobs, sorted by start time", F)
plotProgressByTime(gatkReportData)
# plots summarizing overall costs, merging scattered counts
merged.by.scatter = mergeScatters(gatkReportData)
plotJobsGantt(merged.by.scatter, F, "Jobs merged by scatter by start time", T)
merged.as.df = do.call(rbind.data.frame, merged.by.scatter)[,c("analysisName", "runtime")]
merged.as.df$percent = merged.as.df$runtime / sum(merged.as.df$runtime) * 100
merged.as.df.formatted = data.frame(analysisName=merged.as.df$analysisName,runtime=prettyNum(merged.as.df$runtime), percent=prettyNum(merged.as.df$percent,digits=2))
textplot(merged.as.df.formatted[order(merged.as.df$runtime),], show.rownames=F)
title("Total runtime for each analysis")
plotTimeByHost(gatkReportData)
for ( group in gatkReportData ) {
#print(group)
plotGroup(group)
}
if ( ! is.na(outputPDF) ) {
dev.off()
if (exists("compactPDF")) {
compactPDF(outputPDF)
}
}
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