Analysis and makeDB script fixed
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Eugen Betke
parent
ccebfee53e
commit
e3090c5c23
@ -30,8 +30,8 @@ connection = dbConnect(SQLite(), dbname=file_db)
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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 where ppn==1 or ppn=4 or ppn=8')
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dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
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dbdata = dbGetQuery(connection,'select * from p')
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dbdata[,"blocksize"] = dbdata$tsize
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summary(dbdata)
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@ -57,30 +57,26 @@ 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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ifaces = unique(data1$iface)
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apis = unique(data1$api)
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for (iface in ifaces) {
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data2 = data1[iface == data1$iface, ]
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print(fs)
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for (api in apis) {
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data2 = data1[api == data1$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$type)
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print(app)
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for (type in types) {
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data4 = data3[type == data3$type, ]
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chunkeds = unique(data4$chunked)
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data = data3[type == data3$type, ]
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for (chunked in chunkeds) {
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data5 = data4[chunked == data4$chunked, ]
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filleds = unique(data4$filled)
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for (filled in filleds) {
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data6 = data5[filled == data5$filled, ]
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unlimiteds = unique(data5$unlimited)
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for (unlimited in unlimiteds) {
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data = data6[unlimited == data5$unlimited, ]
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print(type)
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ggplot(data=data, aes(x=nn, y=write, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
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#ggtitle("Write") +
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@ -93,13 +89,13 @@ data = data6[unlimited == data5$unlimited, ]
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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="max", 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_CHUNK:%s_FILL:%s_LIM:%s_%s.eps", folder_out, app, fs, iface, type, chunked, filled, unlimited, "write")
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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")
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ggsave(filename_png, width = 6, height = 4)
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ggsave(filename_eps, width = 6, height = 4)
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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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@ -114,30 +110,14 @@ data = data6[unlimited == data5$unlimited, ]
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scale_x_continuous(breaks = c(unique(data$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="max", 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_CHUNK:%s_FILL:%s_LIM:%s_%s.eps", folder_out, app, fs, iface, type, chunked, filled, unlimited, "read")
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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")
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ggsave(filename_png, width = 6, height = 4)
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ggsave(filename_eps, width = 6, height = 4)
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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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#ggplot(data=data, aes(x=blocksize, y=read, colour=app, group=blocksize)) +
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# ggtitle("Read") +
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# facet_grid(ppn ~ nn, labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
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# xlab("Blocksize in KiB") +
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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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# scale_y_log10() +
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# scale_x_log10(breaks = breaks, labels=breaks/1024) +
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# geom_boxplot()
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##geom_line() +
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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, iface, type, "read")
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#ggsave(filename_eps, width = 8, height = 6)
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##system(sprintf("epstopdf %s", filename_eps))
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}}}}}}}
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}}}}
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7
mkdb.py
7
mkdb.py
@ -33,6 +33,9 @@ def parse(filename, conn):
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metadata["ppn"] = int(m.group(3))
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metadata["api"] = m.group(4)
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metadata["tsize"] = m.group(5)
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metadata["fs"] = "lustre"
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metadata["app"] = "ior-default"
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metadata["type"] = "random"
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else:
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print('couldn\'t parse', os.path.basename(filename))
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@ -75,7 +78,7 @@ def parse(filename, conn):
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for iteration,entry in data.items():
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if len(entry) == 19:
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if len(entry) == 22:
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print("Success")
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columns = ", ".join(entry.keys())
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placeholders = ':' + ', :'.join(entry.keys())
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@ -103,6 +106,8 @@ try:
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nn int, \
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ppn int, \
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api text, \
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fs text, \
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type text, \
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tsize float, \
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fsize float, \
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fsize_ctl txt, \
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