TestON/JenkinsFile/wikiGraphRScripts/SCPFspecificGraphRScripts/SCPFscaleTopo.R

# 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/>.
#
# Example script:
# Scale Topology Latency Test Graph (https://jenkins.onosproject.org/view/QA/job/postjob-BM/lastSuccessfulBuild/artifact/SCPFscaleTopo_master_graph.jpg):
# Rscript SCPFspecificGraphRScripts/SCPFscaleTopo.R <url> <port> <username> <pass> SCPFscaleTopo master /path/to/save/directory/

# **********************************************************
# STEP 1: Data management.
# **********************************************************

print( "**********************************************************" )
print( "STEP 1: Data management." )
print( "**********************************************************" )

save_directory = 7

# Command line arguments are read.
print( "Reading commmand-line args." )
args <- commandArgs( trailingOnly=TRUE )

# ----------------
# Import Libraries
# ----------------

print( "Importing libraries." )
library( ggplot2 )
library( reshape2 )
library( RPostgreSQL )    # For databases
source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/saveGraph.R" )
source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/fundamentalGraphData.R" )
source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/initSQL.R" )
source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/cliArgs.R" )

# -------------------
# Check CLI Arguments
# -------------------

print( "Verifying CLI args." )

if ( length( args ) != save_directory ){
    usage( "SCPFscaleTopo.R" )
    quit( status = 1 )
}

# -----------------
# Create File Names
# -----------------

print( "Creating filenames and title of graph." )

outputFile <- paste( args[ save_directory ],
                     args[ graph_title ],
                     "_",
                     args[ branch_name ],
                     "_graph.jpg",
                     sep="" )

chartTitle <- "Scale Topology Latency Test"

# ------------------
# SQL Initialization
# ------------------

print( "Initializing SQL" )

con <- initSQL( args[ database_host ],
                args[ database_port ],
                args[ database_u_id ],
                args[ database_pw ] )

# --------------------------
# Scale Topology SQL Command
# --------------------------

print( "Generating Scale Topology SQL Command" )

command <- paste( "SELECT * FROM scale_topo_latency_details WHERE branch = '",
                  args[ branch_name ],
                  "' AND date IN ( SELECT MAX( date ) FROM scale_topo_latency_details WHERE branch = '",
                  args[ branch_name ],
                  "' ) ",
                  sep = "" )

fileData <- retrieveData( con, command )

# **********************************************************
# STEP 2: Organize data.
# **********************************************************

print( "**********************************************************" )
print( "STEP 2: Organize Data." )
print( "**********************************************************" )

latestBuildDate <- fileData$date[1]

# ------------
# Data Sorting
# ------------

print( "Sorting data." )

requiredColumns <- c( "last_role_request_to_last_topology", "last_connection_to_last_role_request", "first_connection_to_last_connection" )

tryCatch( avgs <- c( fileData[ requiredColumns] ),
          error = function( e ) {
              print( "[ERROR] One or more expected columns are missing from the data. Please check that the data and SQL command are valid, then try again." )
              print( "Required columns: " )
              print( requiredColumns )
              print( "Actual columns: " )
              print( names( fileData ) )
              print( "Error dump:" )
              print( e )
              quit( status = 1 )
          }
         )

# --------------------
# Construct Data Frame
# --------------------

print( "Constructing Data Frame" )

# Parse lists into data frames.
dataFrame <- melt( avgs )
dataFrame$scale <- fileData$scale
colnames( dataFrame ) <- c( "s",
                            "type",
                            "scale")

# 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$type ) )
dataFrame$iterative <- seq( 1, nrow( fileData ), by = 1 )

dataFrame <- na.omit( dataFrame )   # Omit any data that doesn't exist

sum <- fileData[ 'last_role_request_to_last_topology' ] +
       fileData[ 'last_connection_to_last_role_request' ] +
       fileData[ 'first_connection_to_last_connection' ]

print( "Data Frame Results:" )
print( dataFrame )

# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************

print( "**********************************************************" )
print( "STEP 3: Generate Graph." )
print( "**********************************************************" )

# ------------------
# Generate Main Plot
# ------------------

print( "Creating main plot." )

mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
                                           y = s,
                                           fill = type ) )

# ------------------------------
# Fundamental Variables Assigned
# ------------------------------

print( "Generating fundamental graph data." )

defaultTextSize()
xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative,
                                    label = dataFrame$scale )
xLabel <- xlab( "Scale" )
yLabel <- ylab( "Latency (s)" )
fillLabel <- labs( fill="Type" )

width <- 0.6  # Width of the bars.

theme <- graphTheme()

colors <- scale_fill_manual( values=c( webColor( "redv2" ),
                                       webColor( "green" ),
                                       webColor( "light_blue" ) ) )

values <- geom_text( aes( x = dataFrame$iterative,
                          y = sum + 0.02 * max( sum ),
                          label = format( sum,
                                          big.mark = ",",
                                          scientific = FALSE ),
                          fontface = "bold" ),
                          size = 7.0 )

wrapLegend <- guides( fill = guide_legend( nrow=2, byrow=TRUE ) )

title <- labs( title = chartTitle, subtitle = lastUpdatedLabel( latestBuildDate ) )

# Store plot configurations as 1 variable
fundamentalGraphData <- mainPlot +
                        xScaleConfig +
                        xLabel +
                        yLabel +
                        fillLabel +
                        theme +
                        values +
                        wrapLegend +
                        title +
                        colors

# ---------------------------
# Generating Bar Graph Format
# ---------------------------

print( "Generating bar graph." )

barGraphFormat <- geom_bar( stat = "identity", width = width )

result <- fundamentalGraphData +
          barGraphFormat

# -----------------------
# Exporting Graph to File
# -----------------------

saveGraph( outputFile )
quit( status = 0 )