Difference between revisions of "Sar/Visualize CPU data"

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library( ggplot2 )
library( ggplot2 )
cpu.data <- read.csv( file="<sadf output>", sep=";" )
cpu.data <- read.csv( file="<span class="input"><sadf-output></span>", sep=";" )
cpu.data$timestamp <- as.POSIXct( cpu.data$timestamp )
cpu.data$timestamp <- as.POSIXct( cpu.data$timestamp )
cpu.data$CPU[ cpu.data$CPU == "-1" ] <- "all"
cpu.data$CPU[ cpu.data$CPU == "-1" ] <- "all"

Revision as of 20:41, 8 June 2014

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.

sadf -t -d -P ALL <sar-file> > <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"
ggplot( data=cpu.data, aes( x=timestamp, y=user, group=CPU, colour=CPU ) ) + geom_line()