mirror of
https://github.com/clearlinux/cloud-native-setup.git
synced 2026-09-06 05:41:40 +00:00
fixing indexing, start with 0
This commit is contained in:
David Lyle
committed by
Graham Whaley
Graham Whaley
parent
85fe594c20
commit
15ab28deaf
@@ -57,24 +57,27 @@ for (currentdir in resultdirs) {
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testname=datasetname
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cdata=data.frame(boot_time=as.numeric(fdata$BootResults$launch_time$Result)/1000)
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cdata=cbind(cdata, num_pods=as.numeric(fdata$BootResults$n_pods$Result))
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# format the utilization data
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udata=data.frame(nodename=fdata$BootResults$node_util)
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for (i in seq(length(cdata[, "boot_time"]))) {
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num_pods=fdata$BootResults$n_pods$Result[i]
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index=i-1
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if (i == 1) {
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# first iteration provide column name for c1
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c1=cbind(node=udata$nodename.node)
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c2=cbind(udata$nodename.noschedule)
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c3=cbind(udata$nodename.cpu_idle$Result)
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c4=cbind(udata$nodename.mem_free$Result)/(1024*1024)
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c5=cbind(rep(i, length(udata$nodename.node)))
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c6=cbind(rep(testname, length(udata$nodename.node)))
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c2=cbind(noschedule=udata$nodename.noschedule)
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c3=cbind(cpu_idle=udata$nodename.cpu_idle$Result)
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c4=cbind(mem_free=udata$nodename.mem_free$Result)/(1024*1024)
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# using index to make chart start with 0 rather than 1
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c5=cbind(pod=rep(num_pods, length(udata$nodename.node)))
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c6=cbind(testname=rep(testname, length(udata$nodename.node)))
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# declare formatted utility data
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fudata=cbind(c1,c2,c3,c4,c5,c6)
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}
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else {
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# shift to 0 based indexing
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index=i-1
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sindex=(index*4)+1
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eindex=sindex+3
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# grab 3 columns for next row bind
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@@ -83,14 +86,14 @@ for (currentdir in resultdirs) {
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c2=cbind(row[,2])
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c3=cbind(row[,3]$Result)
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c4=cbind(row[,4]$Result)/(1024*1024)
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c5=cbind(rep(i, length(udata$nodename.node)))
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# using index to make chart start with 0 rather than 1
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c5=cbind(rep(num_pods, length(udata$nodename.node)))
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c6=cbind(rep(testname, length(udata$nodename.node)))
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# create the new row (which is actually the number of nodes of rows)
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frow=cbind(c1,c2,c3,c4,c5,c6)
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fudata=rbind(fudata,frow)
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}
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}
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colnames(fudata)=c("node", "noschedule", "cpu_idle", "mem_free", "pod", "testname")
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# fudata is considered a vector for some reason so converting it to a data.frame
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fudata=as.data.frame(fudata)
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# get unique node names
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@@ -113,44 +116,43 @@ for (currentdir in resultdirs) {
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# format the pod data from 2 nested columns in a series
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# of index specific columns to just 2 columns
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pdata=data.frame(fdata$BootResults$launched_pods)
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# omitting the first row as it is the baseline and contains
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# NA values for launched pods as there were none. If we don't
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# omit the first row, this will throw a warning, but notice that it
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# makes the index funky below
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pdata=data.frame(fdata$BootResults$launched_pods[-1])
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pudata=c()
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for (i in seq(length(cdata[, "boot_time"]))) {
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if (i == 1) {
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# there are no valid values for this index, skipping
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next
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}
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else {
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# shift to 0 based indexing
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index=i-1
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sindex=(index*2)+1
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eindex=sindex+1
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row=cbind(pdata[,sindex:eindex])
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c1=cbind(podname=row[,1])
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c2=cbind(node=row[,2])
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c3=cbind(count=rep(i, length(pdata$pod_name)))
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c4=cbind(boot_time=rep(cdata[, "boot_time"][i],length(pdata$pod_name)))
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c5=cbind(dataset=rep(testname, length(pdata$pod_name)))
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prow=cbind(c1,c2,c3,c4,c5)
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pudata=rbind(pudata,prow)
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}
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# pdata is 1 row shorter than cdata, hence the subtract 1
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for (i in seq(length(cdata[, "boot_time"]) - 1)) {
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# using i+1 rather than i to account for the missing row when indexing in to fdata
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num_pods=fdata$BootResults$n_pods$Result[i+1]
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# shift to 0 based indexing for pdata, so we can iterate through the generated named columns
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index=i-1
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sindex=(index*2)+1
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eindex=sindex+1
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row=cbind(pdata[,sindex:eindex])
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c1=cbind(podname=row[,1])
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c2=cbind(node=row[,2])
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c3=cbind(count=rep(num_pods, length(pdata$pod_name)))
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# using i+1 rather than i to account for the missing row when indexing in to cdata
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c4=cbind(boot_time=rep(cdata[, "boot_time"][i+1],length(pdata$pod_name)))
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c5=cbind(dataset=rep(testname, length(pdata$pod_name)))
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prow=cbind(c1,c2,c3,c4,c5)
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pudata=rbind(pudata,prow)
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}
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# pndata is considered a vector for some reason so converting it to a data.frame
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pudata=as.data.frame(pudata)
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pudata$count=as.numeric(as.character(pudata$count))
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pudata$boot_time=as.numeric(as.character(pudata$boot_time))
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cdata=cbind(cdata, count=seq_len(length(cdata[, "boot_time"])))
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# using 0 based index rather than starting with 1
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cdata=cbind(cdata, testname=rep(testname, length(cdata[, "boot_time"]) ))
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cdata=cbind(cdata, dataset=rep(datasetname, length(cdata[, "boot_time"]) ))
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# Gather our statistics
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# '-1' containers, as the first entry should be a data capture of before
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# the first container was run.
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# FIXME - once the test starts to store a stats baseline in slot 0, then
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# we should re-enable the '-1'
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#sdata=data.frame(num_containers=length(cdata[, "avail_gb"])-1)
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sdata=data.frame(num_containers=length(cdata[, "boot_time"]))
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sdata=data.frame(num_pods=as.numeric(as.character(cdata[, "num_pods"][length(cdata[, "num_pods"])])))
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sudata=c()
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# first (which should be 0-containers)
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for (nodename in nodes) {
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@@ -169,10 +171,13 @@ for (currentdir in resultdirs) {
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as.numeric(as.character(cdata[, node_cpu_idle][length(cdata[, node_cpu_idle])])))
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sudata=rbind(sudata, srdata)
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}
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# now that we have sudata, perform the calculations
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total_pods=as.numeric(as.character(cdata[, "num_pods"][length(cdata[, "num_pods"])]))
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sdata=cbind(sdata, mem_consumed=sum(sudata[, "mem_consumed"]))
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sdata=cbind(sdata, cpu_consumed=sum(sudata[, "cpu_consumed"]))
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sdata=cbind(sdata, boot_time=cdata[, "boot_time"][length(cdata[, "boot_time"])])
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sdata=cbind(sdata, avg_gb_per_c=sdata$mem_consumed / sdata$num_containers)
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sdata=cbind(sdata, avg_gb_per_c=sdata$mem_consumed / total_pods)
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sdata=cbind(sdata, runtime=testname)
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# Store away as a single set
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@@ -183,7 +188,7 @@ for (currentdir in resultdirs) {
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ms = c(
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"Test"=testname,
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"n"=sdata$num_containers,
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"n"=total_pods,
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"size"=round((sdata$mem_consumed), 3),
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"gb/n"=round(sdata$avg_gb_per_c, digits=4),
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"n/Gb"= round(1 / sdata$avg_gb_per_c, digits=2)
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@@ -191,9 +196,9 @@ for (currentdir in resultdirs) {
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cs = c(
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"Test"=testname,
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"n"=sdata$num_containers,
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"n"=total_pods,
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"cpu"=round(sdata$cpu_consumed, digits=3),
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"cpu/n"=round((sdata$cpu_consumed / sdata$num_containers), digits=4)
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"cpu/n"=round((sdata$cpu_consumed / num_pods), digits=4)
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)
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rstats=rbind(rstats, ms)
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@@ -223,7 +228,7 @@ mem_stats_plot = suppressWarnings(ggtexttable(data.frame(rstats),
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mem_line_plot <- ggplot(data=fndata, aes(as.numeric(as.character(pod)),
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as.numeric(as.character(mem_free)),
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colour=(if (num_test_runs > 1) testname else node),
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group=interaction(testname, node))) +
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group=interaction(testname, node))) +
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labs(colour=colour_label) +
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geom_line(alpha=0.2) +
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geom_point(aes(shape=node), alpha=0.3, size=0.5) +
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@@ -240,7 +245,7 @@ cpu_stats_plot = suppressWarnings(ggtexttable(data.frame(cstats), theme=ttheme(b
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cpu_line_plot <- ggplot(data=fndata, aes(as.numeric(as.character(pod)),
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as.numeric(as.character(cpu_idle)),
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colour=(if (num_test_runs > 1) testname else node),
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group=interaction(testname, node))) +
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group=interaction(testname, node))) +
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labs(colour=colour_label) +
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geom_line(alpha=0.2) +
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geom_point(aes(shape=node), alpha=0.3, size=0.5) +
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@@ -252,7 +257,7 @@ cpu_line_plot <- ggplot(data=fndata, aes(as.numeric(as.character(pod)),
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# Show how boot time changed
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boot_line_plot <- ggplot() +
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geom_line( data=data, aes(count, boot_time, colour=testname, group=dataset), alpha=0.2) +
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geom_line( data=data, aes(num_pods, boot_time, colour=testname, group=dataset), alpha=0.2) +
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geom_point( data=pndata, aes(count, boot_time, colour=interaction(dataset, node), group=dataset), alpha=0.6, size=0.6, stroke=0, shape=16) +
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xlab("pods") +
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ylab("Boot time (s)") +
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