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