blob: fd24c8d44b130f941e1e791631da87e3afc7085f [file] [log] [blame]
# Copyright 2017 Open Networking Foundation (ONF)
#
# Please refer questions to either the onos test mailing list at <onos-test@onosproject.org>,
# the System Testing Plans and Results wiki page at <https://wiki.onosproject.org/x/voMg>,
# or the System Testing Guide page at <https://wiki.onosproject.org/x/WYQg>
#
# TestON is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# TestON is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with TestON. If not, see <http://www.gnu.org/licenses/>.
#
# If you have any questions, or if you don't understand R,
# please contact Jeremy Ronquillo: j_ronquillo@u.pacific.edu
# **********************************************************
# STEP 1: File management.
# **********************************************************
print( "STEP 1: File management." )
# Command line arguments are read.
print( "Reading commmand-line args." )
args <- commandArgs( trailingOnly=TRUE )
# Import libraries to be used for graphing and organizing data, respectively.
# Find out more about ggplot2: https://github.com/tidyverse/ggplot2
# reshape2: https://github.com/hadley/reshape
print( "Importing libraries." )
library( ggplot2 )
library( reshape2 )
library( RPostgreSQL ) # For databases
# Check if sufficient args are provided.
if ( is.na( args[ 7 ] ) ){
print( "Usage: Rscript SCPFportLat <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
q() # basically exit(), but in R
}
# paste() is used to concatenate strings.
errBarOutputFileUp <- paste( args[ 7 ], "SCPFportLat_", sep = "" )
errBarOutputFileUp <- paste( errBarOutputFileUp, args[ 6 ], sep = "" )
errBarOutputFileUp <- paste( errBarOutputFileUp, "_UpErrBarWithStack.jpg", sep = "" )
errBarOutputFileDown <- paste( args[ 7 ], "SCPFportLat_", sep = "" )
errBarOutputFileDown <- paste( errBarOutputFileDown, args[ 6 ], sep = "" )
errBarOutputFileDown <- paste( errBarOutputFileDown, "_DownErrBarWithStack.jpg", sep = "" )
print( "Reading from databases." )
con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
command <- paste( "SELECT * FROM port_latency_details WHERE branch = '", args[ 6 ], sep = "" )
command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM port_latency_details WHERE branch = '", sep = "" )
command <- paste( command, args[ 6 ], sep = "" )
command <- paste( command, "' ) ", sep="" )
print( paste( "Sending SQL command:", command ) )
fileData <- dbGetQuery( con, command )
chartTitle <- paste( "Port Latency", args[ 6 ], sep = " - " )
chartTitle <- paste( chartTitle, "\n" )
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
print( "Sorting data." )
upAvgs <- c( fileData[ 'up_ofp_to_dev_avg' ], fileData[ 'up_dev_to_link_avg' ], fileData[ 'up_link_to_graph_avg' ] )
upAvgsData <- melt( upAvgs )
upAvgsData$scale <- fileData$scale
upAvgsData$up_std <- fileData$up_std
colnames( upAvgsData ) <- c( "ms", "type", "scale", "stds" )
upAvgsData$type <- as.character( upAvgsData$type )
upAvgsData$type <- factor( upAvgsData$type, levels=unique( upAvgsData$type ) )
downAvgs <- c( fileData[ 'down_ofp_to_dev_avg' ], fileData[ 'down_dev_to_link_avg' ], fileData[ 'down_link_to_graph_avg' ] )
downAvgsData <- melt( downAvgs )
downAvgsData$scale <- fileData$scale
downAvgsData$down_std <- fileData$down_std
colnames( downAvgsData ) <- c( "ms", "type", "scale", "stds" )
downAvgsData$type <- as.character( downAvgsData$type )
downAvgsData$type <- factor( downAvgsData$type, levels=unique( downAvgsData$type ) )
upAvgsData <- na.omit( upAvgsData ) # Omit any data that doesn't exist
downAvgsData <- na.omit( downAvgsData ) # Omit any data that doesn't exist
print( "Up Averages Results:" )
print( upAvgsData )
print( "Down Averages Results:" )
print( downAvgsData )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
print( "Generating fundamental graph data (Port Up Latency)." )
width <- 1
theme_set( theme_grey( base_size = 20 ) ) # set the default text size of the graph.
mainPlot <- ggplot( data = upAvgsData, aes( x = scale, y = ms, fill = type, ymin = fileData[ 'up_end_to_end_avg' ] - stds, ymax = fileData[ 'up_end_to_end_avg' ] + stds ) )
xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
xLabel <- xlab( "Scale" )
yLabel <- ylab( "Latency (ms)" )
fillLabel <- labs( fill="Type" )
theme <- theme( plot.title=element_text( hjust = 0.5, size = 28, face='bold' ) )
fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
print( "Generating bar graph with error bars (Port Up Latency)." )
barGraphFormat <- geom_bar( stat="identity", width = width )
errorBarFormat <- geom_errorbar( width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) )
sum <- fileData[ 'up_ofp_to_dev_avg' ] + fileData[ 'up_dev_to_link_avg' ] + fileData[ 'up_link_to_graph_avg' ]
values <- geom_text( aes( x=upAvgsData$scale, y=sum + 0.04 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 5, fontface = "bold" )
title <- ggtitle( "Port Up Latency" )
result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values
print( paste( "Saving bar chart with error bars (Port Up Latency) to", errBarOutputFileUp ) )
ggsave( errBarOutputFileUp, width = 10, height = 6, dpi = 200 )
print( paste( "Successfully wrote bar chart with error bars (Port Up Latency) out to", errBarOutputFileUp ) )
print( "Generating fundamental graph data (Port Down Latency)." )
mainPlot <- ggplot( data = downAvgsData, aes( x = scale, y = ms, fill = type, ymin = fileData[ 'down_end_to_end_avg' ] - stds, ymax = fileData[ 'down_end_to_end_avg' ] + stds ) )
theme <- theme( plot.title=element_text( hjust = 0.5, size = 28, face='bold' ) )
fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
print( "Generating bar graph with error bars (Port Down Latency)." )
barGraphFormat <- geom_bar( stat="identity", width = width )
errorBarFormat <- geom_errorbar( width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) )
sum <- fileData[ 'down_ofp_to_dev_avg' ] + fileData[ 'down_dev_to_link_avg' ] + fileData[ 'down_link_to_graph_avg' ]
values <- geom_text( aes( x=downAvgsData$scale, y=sum + 0.04 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 5, fontface = "bold" )
title <- ggtitle( "Port Down Latency" )
result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values
print( paste( "Saving bar chart with error bars (Port Down Latency) to", errBarOutputFileDown ) )
ggsave( errBarOutputFileDown, width = 10, height = 6, dpi = 200 )
print( paste( "Successfully wrote bar chart with error bars (Port Down Latency) out to", errBarOutputFileDown ) )