143 lines
4.5 KiB
R
Executable File
143 lines
4.5 KiB
R
Executable File
#!/usr/bin/env Rscript
|
|
|
|
library(sqldf)
|
|
library(plyr)
|
|
library(plot3D)
|
|
library(ggplot2)
|
|
|
|
|
|
args = commandArgs(trailingOnly=TRUE)
|
|
print(args)
|
|
if (2 != length(args)) {
|
|
print("Requires 2 parameters)")
|
|
q()
|
|
}
|
|
|
|
file_db = args[1]
|
|
folder_out = args[2]
|
|
print(file_db)
|
|
|
|
make_facet_label <- function(variable, value){
|
|
return(paste0(value, " KiB"))
|
|
}
|
|
|
|
|
|
#connection = dbConnect(SQLite(), dbname='results.ddnime.db')
|
|
print(file_db)
|
|
connection = dbConnect(SQLite(), dbname=file_db)
|
|
|
|
#dbdata = dbGetQuery(connection,'select mnt, siox, avg(duration) as ad, app, procs, blocksize from p group by mnt, siox, procs, blocksize, app')
|
|
#dbdata = dbGetQuery(connection,'select * from p where tag=="mpio-individual"')
|
|
#dbdata = dbGetQuery(connection,'select *, (x*y*z) as blocksize from p where count=8')
|
|
#dbdata = dbGetQuery(connection,'select * from p where count<5')
|
|
dbdata = dbGetQuery(connection,'select * from p where (ppn==1 or ppn=4 or ppn=8) and striping="yes"' )
|
|
dbdata[,"blocksize"] = dbdata$tsize
|
|
|
|
|
|
summary(dbdata)
|
|
|
|
nn_lab <- sprintf(fmt="NN=%d", unique(dbdata$nn))
|
|
names(nn_lab) <- unique(dbdata$nn)
|
|
ppn_lab <- sprintf(fmt="PPN=%d", unique(dbdata$ppn))
|
|
names(ppn_lab) <- unique(dbdata$ppn)
|
|
breaks <- c(unique(dbdata$blocksize))
|
|
|
|
|
|
dbdata$lab_access <- dbdata$accesstype
|
|
dbdata$lab_access[dbdata$lab_access == "write"] = "Write"
|
|
dbdata$lab_access[dbdata$lab_access == "read"] = "Read"
|
|
|
|
|
|
|
|
fig_w = 4
|
|
fig_h = 4
|
|
|
|
w = c(4, 6, 4)
|
|
h = c(4, 4, 4)
|
|
event = c("paper", "isc-pres", "poster")
|
|
dims_list = data.frame(h, w, event) # df is a data frame
|
|
|
|
|
|
|
|
for (scale in c("linear", "logarithmic")) {
|
|
|
|
|
|
|
|
fss = unique(dbdata$fs)
|
|
for (fs in fss) {
|
|
data1 = dbdata[fs == dbdata$fs, ]
|
|
#apis = unique(data1$api)
|
|
|
|
print(fs)
|
|
|
|
#for (api in apis) {
|
|
#data2 = data1[api == data1$api, ]
|
|
apps = unique(data1$app)
|
|
|
|
#print(api)
|
|
|
|
for (app in apps) {
|
|
data3 = data1[app == data1$app, ]
|
|
iotypes = unique(data3$iotype)
|
|
|
|
print(app)
|
|
|
|
for (iotype in iotypes) {
|
|
data = data3[iotype == data3$iotype, ]
|
|
|
|
print(iotype)
|
|
|
|
p = ggplot(data=data, aes(x=nn, y=perf, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
|
|
#ggtitle("Write") +
|
|
facet_grid(ppn ~ api + lab_access, labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
|
|
xlab("Nodes") +
|
|
ylab("Performance in MiB/s") +
|
|
theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
|
|
theme(legend.position="bottom") +
|
|
#scale_x_continuous(breaks = c(unique(data$nn))) +
|
|
scale_x_log10(breaks = c(unique(data$nn))) +
|
|
scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000'), breaks=sort(unique(data$blocksize)/1024)) +
|
|
#stat_summary(fun.y="median", geom="line", aes(group=factor(blocksize))) +
|
|
stat_summary(fun.y="mean", geom="line", aes(group=factor(blocksize))) +
|
|
#geom_boxplot()
|
|
geom_point()
|
|
|
|
if ( "logarithmic" == scale ) {
|
|
p = p + scale_y_log10()
|
|
}
|
|
|
|
filename_eps = sprintf("%s/performance_%s_%s_%s_%s_%s.eps", folder_out, app, fs, iotype, "write", scale)
|
|
filename_png = sprintf("%s/performance_%s_%s_%s_%s_%s.png", folder_out, app, fs, iotype, "write", scale)
|
|
ggsave(filename_png, width = 10, height = 8)
|
|
ggsave(filename_eps, width = 10, height = 8)
|
|
#system(sprintf("epstopdf %s", filename_eps))
|
|
system(sprintf("rm %s", filename_eps))
|
|
|
|
#p = ggplot(data=data, aes(x=nn, y=read, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
|
|
# #ggtitle("Read") +
|
|
# facet_grid(ppn ~ ., labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
|
|
# xlab("Nodes") +
|
|
# ylab("Performance in MiB/s") +
|
|
# theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
|
|
# theme(legend.position="bottom") +
|
|
# #scale_x_continuous(breaks = c(unique(data$nn))) +
|
|
# scale_x_log10(breaks = c(unique(data$nn))) +
|
|
# scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000'), breaks=sort(unique(data$blocksize)/1024)) +
|
|
# #stat_summary(fun.y="median", geom="line", aes(group=factor(blocksize))) +
|
|
# stat_summary(fun.y="mean", geom="line", aes(group=factor(blocksize))) +
|
|
# #geom_boxplot()
|
|
# geom_point()
|
|
|
|
#if ( "logarithmic" == scale ) {
|
|
# p = p + scale_y_log10()
|
|
#}
|
|
|
|
#filename_eps = sprintf("%s/performance_%s_%s_%s_%s_%s_%s.eps", folder_out, app, fs, api, type, "read", scale)
|
|
#filename_png = sprintf("%s/performance_%s_%s_%s_%s_%s_%s.png", folder_out, app, fs, api, type, "read", scale)
|
|
#ggsave(filename_png, width = 3, height = 10)
|
|
#ggsave(filename_eps, width = 3, height = 10)
|
|
##system(sprintf("epstopdf %s", filename_eps))
|
|
#system(sprintf("rm %s", filename_eps))
|
|
|
|
}}}}
|