Useful scripts to collect/display perf results.

Add shell scripts to make it easier to collect performance results from
traces, live tests, and phoronix tests.

With run_performance_tests.sh you specify the following:
  - a subject program to run, using --root
  - a name to give to this set of results, using --variant
  - a test to run, using --test
  - a file to write the results to, using --results.

For tests that start with "trace", the script runs falco/sysdig on the
trace file and measures the time taken to read the file. For other
tests, he script handles starting falco/sysdig, starting a cpu
measurement script (a wrapper around top, just to provide identical
values to what you would see using top) to measure the cpu usage of
falco/sysdig, and running a live test.

The measurement interval for cpu usage depends on the test being run--10
seconds for most tests, 2 seconds for shorter tests.

The output is written as json to the file specified in --results.

Also add R scripts to easily display the results from the shell
script. plot-live.r shows a linechart of the cpu usage for the provided
variants over time. plot-traces.r shows grouped barcharts showing
user/system/total time taken for the provided variants and traces.

One bug--you have to make the results file actual json by adding
leading/trailing []s.

test/plot-live.r

@@ -0,0 +1,40 @@
+require(jsonlite)
+library(ggplot2)
+library(GetoptLong)
+
+initial.options <- commandArgs(trailingOnly = FALSE)
+file.arg.name <- "--file="
+script.name <- sub(file.arg.name, "", initial.options[grep(file.arg.name, initial.options)])
+script.basename <- dirname(script.name)
+
+if (substr(script.basename, 1, 1) != '/') {
+    script.basename = paste(getwd(), script.basename, sep='/')
+}
+
+results = paste(script.basename, "results.json", sep='/')
+output = "./output.png"
+
+GetoptLong(
+    "results=s", "Path to results file",
+    "benchmark=s", "Benchmark from results file to graph",
+    "variant=s@", "Variant(s) to include in graph. Can be specified multiple times",
+    "output=s", "Output graph file"
+)
+
+res <- fromJSON(results, flatten=TRUE)
+
+res2 = res[res$benchmark == benchmark & res$variant %in% variant,]
+
+plot <- ggplot(data=res2, aes(x=sample, y=cpu_usage, group=variant, colour=variant)) +
+    geom_line() +
+    ylab("CPU Usage (%)") +
+    xlab("Time") +
+    ggtitle(sprintf("Falco/Sysdig CPU Usage: %s", benchmark))
+    theme(legend.position=c(.2, .88));
+
+print(paste("Writing graph to", output, sep=" "))
+ggsave(file=output)
+
+
+
+