Description Usage Arguments Details Author(s) References Examples
View source: R/cloudUtilPlot.R
On the utilization graphic each horizontal line indicates the start and the end of one job. Color groups different runs.
1 2 3 4 5 6 | cloudUtilPlot(group, begin, end, id,
colormap,
normalize,
plotConcurrent,
plotConcurrentMax,
main)
|
begin |
a time series of the starting events; the time format is unix time stamp (seconds since Jan 01 1970). |
end |
a time series of the corresponding ending events. |
id |
identifyer of each event. |
group |
group of each event. |
main |
an overall title for the plot. |
colormap |
color vector for the data. default is the rainbow colormap having as much colors as we have groups. |
normalize |
normalizes the time in a way that the groups are relative to each other; default is set to TRUE. |
plotConcurrent |
plot concurrent running tasks as solid lines; default is set to TRUE. |
plotConcurrentMax |
plot maximum of concurrent running tasks; default is set to FALSE. |
The cloudUtilPlot
function reqires the four arguments begin
,
end
, group
, and id
. All other arguments are optional.
Christian Panse
Tyanko Aleksiev, Simon Barkow, Peter Kunszt, Sergio Maffioletti, Riccardo Murri, Christian Panse (2013), VM-MAD: a cloud/cluster software for service-oriented academic environments, https://arxiv.org/abs/1302.2529.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | data(cloudms2)
#green
col.amazon<-rgb(0.1,0.8,0.1,alpha=0.2)
col.amazon2<-rgb(0.1,0.8,0.1,alpha=0.2)
#blue
col.fgcz<-rgb(0.1,0.1,0.8,alpha=0.2)
col.fgcz2<-rgb(0.1,0.1,0.5,alpha=0.2)
#red
col.uzh<-rgb(0.8,0.1,0.1,alpha=0.2)
col.uzh2<-rgb(0.5,0.1,0.1,alpha=0.2)
cm<-c(col.amazon, col.amazon2, col.fgcz, col.fgcz2, col.uzh, col.uzh2)
cloudUtilPlot(begin=cloudms2$BEGIN_PROCESS,
end=cloudms2$END_PROCESS,
id=cloudms2$id,
group=cloudms2$CLOUD,
colormap=cm,
normalize=FALSE,
plotConcurrent=TRUE);
cloudUtilPlot(begin=cloudms2$BEGIN_PROCESS,
end=cloudms2$END_PROCESS,
id=cloudms2$id,
group=cloudms2$CLOUD,
colormap=cm,
normalize=TRUE,
plotConcurrent=TRUE)
|
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