Visualize sar CPU data with R

This is a five minute guide how to visualize Linux's sar data provided by the sysstat utility without a lot of mangeling the data.

Goal

Create CPU graphs in R from the sar utility without massaging the output data too much.

Prerequisites

• The Linux sysstat package installed and configured to report performance data.
• R
• ggplot2 R library

Howto

Dumping the sar data with sadf

The data sar collects is in binary format and needs to be converted first to a format that can be imported into R. This is done with the sadf command which converts the collected data into tabular data delimited by semicolon.
Note: On CentOS 6 and higher the sadf command also prints a header file to make most use of it we need to slightly changes it like remove the leading #, plus remove the % from the cpu data but only in the first. Other lines starting with # or containing a LINUX-RESTART should also be removed. Your milage may vary!

sadf -t -d -P ALL <SAR-FILE> | \
  sed -e '1,1s/\(^#\|%\)//g' \
      -e '/\(^#\|LINUX-RESTART\)/d' \
  > <SADF-OUTPUT>

Importing the data into R

The next step is to read the tabular data into R and print the graphs there are just a handful of commands to do this. In R type the following commands.

library( ggplot2 )
cpu.data <- read.csv( file="<SADF-OUTPUT>", sep=";" )
cpu.data$timestamp <- as.POSIXct( cpu.data$timestamp )
cpu.data$CPU[ cpu.data$CPU == "-1" ] <- "all"
cpu.graph <- ggplot( data=cpu.data, aes( x=timestamp, y=user, group=CPU, colour=CPU ) )
cpu.graph + geom_line() 

Will result in a graph like this:

Plotting each CPU separately

To show which CPU or core is used most it is probably better to separately print the CPUs. The ggplot2 library comes with a nifty command called facet_grid(). To print each separately simply add it to the end of the previous command.

cpu.graph + geom_line() + facet_grid( CPU~. ) 

Which will result in a graph like this.

Saving the graph to a file

Especially when automation comes into play saving to a file is a must this example shows how to save to PNG.

 setwd( "/home/r-user/cpu-data" )
 png( "cpu-graph-grid.png", width=600, height=360, res=72 )
 cpu.graph + geom_line() + facet_grid( CPU~. )  
 dev.off()