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# 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 SCPFbatchFlowResp <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.
errBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
errBarOutputFile <- paste( errBarOutputFile, args[ 6 ], sep="_" )
errBarOutputFile <- paste( errBarOutputFile, "_PostGraph.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 batch_flow_tests WHERE branch='", args[ 6 ], sep="" )
command <- paste( command, "' ORDER BY date DESC LIMIT 3", sep="" )
print( paste( "Sending SQL command:", command ) )
fileData <- dbGetQuery( con, command )
chartTitle <- paste( "Single Bench Flow Latency - Post", "Last 3 Builds", sep = "\n" )
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
avgs <- c()
print( "Sorting data." )
avgs <- c( fileData[ 'posttoconfrm' ], fileData[ 'elapsepost' ] )
dataFrame <- melt( avgs )
dataFrame$scale <- fileData$scale
dataFrame$date <- fileData$date
dataFrame$iterative <- dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
colnames( dataFrame ) <- c( "ms", "type", "scale", "date", "iterative" )
# Format data frame so that the data is in the same order as it appeared in the file.
dataFrame$type <- as.character( dataFrame$type )
dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
print( "Data Frame Results:" )
print( dataFrame )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
print( "Generating fundamental graph data." )
theme_set( theme_grey( base_size = 20 ) ) # set the default text size of the graph.
mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = ms, fill = type ) )
xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
xLabel <- xlab( "Build Date" )
yLabel <- ylab( "Latency (ms)" )
fillLabel <- labs( fill="Type" )
theme <- theme( plot.title=element_text( hjust = 0.5, size = 28, face='bold' ) )
fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
print( "Generating bar graph." )
width <- 0.3
barGraphFormat <- geom_bar( stat="identity", width = width )
sum <- fileData[ 'posttoconfrm' ] + fileData[ 'elapsepost' ]
values <- geom_text( aes( x=dataFrame$iterative, y=sum + 0.04 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 5, fontface = "bold" )
title <- ggtitle( chartTitle )
result <- fundamentalGraphData + barGraphFormat + title + values
print( paste( "Saving bar chart to", errBarOutputFile ) )
ggsave( errBarOutputFile, width = 10, height = 6, dpi = 200 )
print( paste( "Successfully wrote stacked bar chart out to", errBarOutputFile ) )
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
avgs <- c()
print( "Sorting data." )
avgs <- c( fileData[ 'deltoconfrm' ], fileData[ 'elapsedel' ] )
dataFrame <- melt( avgs )
dataFrame$scale <- fileData$scale
dataFrame$date <- fileData$date
dataFrame$iterative <- dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
colnames( dataFrame ) <- c( "ms", "type", "scale", "date", "iterative" )
# Format data frame so that the data is in the same order as it appeared in the file.
dataFrame$type <- as.character( dataFrame$type )
dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
print( "Data Frame Results:" )
print( dataFrame )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
print( "Generating fundamental graph data." )
theme_set( theme_grey( base_size = 20 ) ) # set the default text size of the graph.
mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = ms, fill = type ) )
xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
xLabel <- xlab( "Build Date" )
yLabel <- ylab( "Latency (ms)" )
fillLabel <- labs( fill="Type" )
theme <- theme( plot.title=element_text( hjust = 0.5, size = 28, face='bold' ) )
fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
print( "Generating bar graph." )
width <- 0.3
barGraphFormat <- geom_bar( stat="identity", width = width )
sum <- fileData[ 'deltoconfrm' ] + fileData[ 'elapsedel' ]
values <- geom_text( aes( x=dataFrame$iterative, y=sum + 0.04 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 5, fontface = "bold" )
chartTitle <- paste( "Single Bench Flow Latency - Del", "Last 3 Builds", sep = "\n" )
title <- ggtitle( chartTitle )
result <- fundamentalGraphData + barGraphFormat + title + values
errBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
errBarOutputFile <- paste( errBarOutputFile, args[ 6 ], sep="_" )
errBarOutputFile <- paste( errBarOutputFile, "_DelGraph.jpg", sep="" )
print( paste( "Saving bar chart to", errBarOutputFile ) )
ggsave( errBarOutputFile, width = 10, height = 6, dpi = 200 )
print( paste( "Successfully wrote stacked bar chart out to", errBarOutputFile ) )