ddn-ime-evaluation/eval_analysis.R

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2018-10-04 14:53:44 +00:00
#!/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')
dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
summary(dbdata)
nn_lab <- sprintf(fmt="NN=%d", unique(dbdata$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))
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
fss = unique(dbdata$fs)
for (fs in fss) {
data1 = dbdata[fs == dbdata$fs, ]
ifaces = unique(data1$iface)
for (iface in ifaces) {
data2 = data1[iface == data1$iface, ]
apps = unique(data2$app)
for (app in apps) {
data3 = data2[app == data2$app, ]
types = unique(data3$type)
for (type in types) {
data4 = data3[type == data3$type, ]
chunkeds = unique(data4$chunked)
for (chunked in chunkeds) {
data5 = data4[chunked == data4$chunked, ]
filleds = unique(data4$filled)
for (filled in filleds) {
data6 = data5[filled == data5$filled, ]
unlimiteds = unique(data5$unlimited)
for (unlimited in unlimiteds) {
data = data6[unlimited == data5$unlimited, ]
ggplot(data=data, aes(x=nn, y=write, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
#ggtitle("Write") +
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_y_log10() +
scale_x_continuous(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="max", geom="line", aes(group=factor(blocksize))) +
#geom_boxplot()
geom_point()
filename_eps = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.eps", folder_out, app, fs, iface, type, chunked, filled, unlimited, "write")
filename_png = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.png", folder_out, app, fs, iface, type, chunked, filled, unlimited, "write")
ggsave(filename_png, width = 6, height = 4)
ggsave(filename_eps, width = 6, height = 4)
system(sprintf("epstopdf %s", filename_eps))
system(sprintf("rm %s", filename_eps))
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_y_log10() +
scale_x_continuous(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="max", geom="line", aes(group=factor(blocksize))) +
#geom_boxplot()
geom_point()
filename_eps = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.eps", folder_out, app, fs, iface, type, chunked, filled, unlimited, "read")
filename_png = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.png", folder_out, app, fs, iface, type, chunked, filled, unlimited, "read")
ggsave(filename_png, width = 6, height = 4)
ggsave(filename_eps, width = 6, height = 4)
system(sprintf("epstopdf %s", filename_eps))
system(sprintf("rm %s", filename_eps))
#ggplot(data=data, aes(x=blocksize, y=read, colour=app, group=blocksize)) +
# ggtitle("Read") +
# facet_grid(ppn ~ nn, labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
# xlab("Blocksize in KiB") +
# ylab("Performance in MiB/s") +
# theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
# scale_y_log10() +
# scale_x_log10(breaks = breaks, labels=breaks/1024) +
# geom_boxplot()
##geom_line() +
##geom_point()
#filename_eps = sprintf("%s/performance_%s_%s_%s_%s_%s.eps", folder_out, app, fs, iface, type, "read")
#ggsave(filename_eps, width = 8, height = 6)
##system(sprintf("epstopdf %s", filename_eps))
}}}}}}}