TestON/JenkinsFile/wikiGraphRScripts/SCPFspecificGraphRScripts/SCPFbatchFlowResp.R - OnosSystemTest - Gitiles

 # 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
 #
 # Example script:
 # Single Bench Flow Latency Graph with Eventually Consistent Flow Rule Store (https://jenkins.onosproject.org/view/QA/job/postjob-BM/lastSuccessfulBuild/artifact/SCPFbatchFlowResp_master_OldFlow_PostGraph.jpg):
 # Rscript SCPFbatchFlowResp.R <url> <port> <username> <pass> SCPFbatchFlowResp.R master y /path/to/save/directory/

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

 old_flow <- 7
 save_directory <- 8

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

 # 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( "dependencies/saveGraph.R" )
 source( "dependencies/fundamentalGraphData.R" )
 source( "dependencies/initSQL.R" )
 source( "dependencies/cliArgs.R" )

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

 print( "Verifying CLI args." )

 if ( length( args ) != save_directory ){
     usage( "SCPFbatchFlowResp.R", c( "using-old-flow" ) )
     quit( status = 1 )
 }

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

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

 postOutputFile <- paste( args[ save_directory ],
                          args[ graph_title ],
                          "_",
                          args[ branch_name ],
                          if( args[ old_flow ] == "y" ) "_OldFlow" else "",
                          "_PostGraph.jpg",
                          sep="" )

 delOutputFile <- paste( args[ save_directory ],
                         args[ graph_title ],
                         "_",
                         args[ branch_name ],
                         if( args[ old_flow ] == "y" ) "_OldFlow" else "",
                         "_DelGraph.jpg",
                         sep="" )

 postChartTitle <- paste( "Single Bench Flow Latency - Post\n",
                          "Last 3 Builds",
                          if( args[ old_flow ] == "y" ) "\nWith Eventually Consistent Flow Rule Store" else "",
                          sep = "" )
 delChartTitle <- paste( "Single Bench Flow Latency - Del\n",
                         "Last 3 Builds",
                         if( args[ old_flow ] == "y" ) "\nWith Eventually Consistent Flow Rule Store" else "",
                         sep = "" )

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

 print( "Initializing SQL" )

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

 # ---------------------------
 # Batch Flow Resp SQL Command
 # ---------------------------

 print( "Generating Batch Flow Resp SQL Command" )

 command <- paste( "SELECT * FROM batch_flow_tests WHERE branch='",
                   args[ branch_name ],
                   "' AND " ,
                   ( if( args[ old_flow ] == 'y' ) "" else "NOT " ) ,
                   "is_old_flow",
                   " ORDER BY date DESC LIMIT 3",
                   sep="" )

 fileData <- retrieveData( con, command )

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

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

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

 print( "Sorting data for Post." )

 requiredColumns <- c( "posttoconfrm", "elapsepost" )

 tryCatch( postAvgs <- 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 )
           }
          )

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

 postDataFrame <- melt( postAvgs )
 postDataFrame$scale <- fileData$scale
 postDataFrame$date <- fileData$date
 postDataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )

 colnames( postDataFrame ) <- c( "ms",
                                 "type",
                                 "scale",
                                 "date",
                                 "iterative" )

 # Format data frame so that the data is in the same order as it appeared in the file.
 postDataFrame$type <- as.character( postDataFrame$type )
 postDataFrame$type <- factor( postDataFrame$type,
                               levels = unique( postDataFrame$type ) )

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

 print( "Post Data Frame Results:" )
 print( postDataFrame )

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

 requiredColumns <- c( "deltoconfrm", "elapsedel" )

 tryCatch( delAvgs <- 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 )
           }
          )


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

 delDataFrame <- melt( delAvgs )
 delDataFrame$scale <- fileData$scale
 delDataFrame$date <- fileData$date
 delDataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )

 colnames( delDataFrame ) <- c( "ms",
                                "type",
                                "scale",
                                "date",
                                "iterative" )

 # Format data frame so that the data is in the same order as it appeared in the file.
 delDataFrame$type <- as.character( delDataFrame$type )
 delDataFrame$type <- factor( delDataFrame$type,
                              levels = unique( delDataFrame$type ) )

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

 print( "Del Data Frame Results:" )
 print( delDataFrame )

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

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

 # ------------------------------------------
 # Initializing variables used in both graphs
 # ------------------------------------------

 print( "Initializing variables used in both graphs." )

 defaultTextSize()
 xLabel <- xlab( "Build Date" )
 yLabel <- ylab( "Latency (ms)" )
 fillLabel <- labs( fill="Type" )

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

 wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )

 barWidth <- 0.3

 theme <- graphTheme()

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

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

 print( "Creating main plot for Post graph." )

 mainPlot <- ggplot( data = postDataFrame, aes( x = iterative,
                                                y = ms,
                                                fill = type ) )

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

 print( "Generating fundamental graph data for Post graph." )

 xScaleConfig <- scale_x_continuous( breaks = postDataFrame$iterative,
                                     label = postDataFrame$date )

 title <- labs( title = postChartTitle, subtitle = lastUpdatedLabel() )

 fundamentalGraphData <- mainPlot +
                         xScaleConfig +
                         xLabel +
                         yLabel +
                         fillLabel +
                         theme +
                         wrapLegend +
                         colors +
                         title

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

 print( "Generating bar graph for Post graph." )

 sum <- fileData[ 'posttoconfrm' ] +
        fileData[ 'elapsepost' ]

 values <- geom_text( aes( x = postDataFrame$iterative,
                           y = sum + 0.03 * max( sum ),
                           label = format( sum,
                                           digits = 3,
                                           big.mark = ",",
                                           scientific = FALSE ) ),
                           size = 7.0,
                           fontface = "bold" )

 result <- fundamentalGraphData +
           barGraphFormat +
           values

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

 saveGraph( postOutputFile )

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

 print( "Creating main plot for Del graph." )

 mainPlot <- ggplot( data = delDataFrame, aes( x = iterative,
                                               y = ms,
                                               fill = type ) )

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

 print( "Generating fundamental graph data for Del graph." )

 xScaleConfig <- scale_x_continuous( breaks = delDataFrame$iterative,
                                     label = delDataFrame$date )

 title <- labs( title = delChartTitle, subtitle = lastUpdatedLabel() )

 fundamentalGraphData <- mainPlot +
                         xScaleConfig +
                         xLabel +
                         yLabel +
                         fillLabel +
                         theme +
                         wrapLegend +
                         colors +
                         title

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

 print( "Generating bar graph for Del graph." )

 sum <- fileData[ 'deltoconfrm' ] +
        fileData[ 'elapsedel' ]

 values <- geom_text( aes( x = delDataFrame$iterative,
                           y = sum + 0.03 * max( sum ),
                           label = format( sum,
                                           digits = 3,
                                           big.mark = ",",
                                           scientific = FALSE ) ),
                           size = 7.0,
                           fontface = "bold" )

 result <- fundamentalGraphData +
           barGraphFormat +
           title +
           values

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

 saveGraph( delOutputFile )
 quit( status = 0 )
	# 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
	#
	# Example script:
	# Single Bench Flow Latency Graph with Eventually Consistent Flow Rule Store (https://jenkins.onosproject.org/view/QA/job/postjob-BM/lastSuccessfulBuild/artifact/SCPFbatchFlowResp_master_OldFlow_PostGraph.jpg):
	# Rscript SCPFbatchFlowResp.R <url> <port> <username> <pass> SCPFbatchFlowResp.R master y /path/to/save/directory/

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

	old_flow <- 7
	save_directory <- 8

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

	# 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( "dependencies/saveGraph.R" )
	source( "dependencies/fundamentalGraphData.R" )
	source( "dependencies/initSQL.R" )
	source( "dependencies/cliArgs.R" )

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

	print( "Verifying CLI args." )

	if ( length( args ) != save_directory ){
	usage( "SCPFbatchFlowResp.R", c( "using-old-flow" ) )
	quit( status = 1 )
	}

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

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

	postOutputFile <- paste( args[ save_directory ],
	args[ graph_title ],
	"_",
	args[ branch_name ],
	if( args[ old_flow ] == "y" ) "_OldFlow" else "",
	"_PostGraph.jpg",
	sep="" )

	delOutputFile <- paste( args[ save_directory ],
	args[ graph_title ],
	"_",
	args[ branch_name ],
	if( args[ old_flow ] == "y" ) "_OldFlow" else "",
	"_DelGraph.jpg",
	sep="" )

	postChartTitle <- paste( "Single Bench Flow Latency - Post\n",
	"Last 3 Builds",
	if( args[ old_flow ] == "y" ) "\nWith Eventually Consistent Flow Rule Store" else "",
	sep = "" )
	delChartTitle <- paste( "Single Bench Flow Latency - Del\n",
	"Last 3 Builds",
	if( args[ old_flow ] == "y" ) "\nWith Eventually Consistent Flow Rule Store" else "",
	sep = "" )

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

	print( "Initializing SQL" )

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

	# ---------------------------
	# Batch Flow Resp SQL Command
	# ---------------------------

	print( "Generating Batch Flow Resp SQL Command" )

	command <- paste( "SELECT * FROM batch_flow_tests WHERE branch='",
	args[ branch_name ],
	"' AND " ,
	( if( args[ old_flow ] == 'y' ) "" else "NOT " ) ,
	"is_old_flow",
	" ORDER BY date DESC LIMIT 3",
	sep="" )

	fileData <- retrieveData( con, command )

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

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

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

	print( "Sorting data for Post." )

	requiredColumns <- c( "posttoconfrm", "elapsepost" )

	tryCatch( postAvgs <- 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 )
	}
	)

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

	postDataFrame <- melt( postAvgs )
	postDataFrame$scale <- fileData$scale
	postDataFrame$date <- fileData$date
	postDataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )

	colnames( postDataFrame ) <- c( "ms",
	"type",
	"scale",
	"date",
	"iterative" )

	# Format data frame so that the data is in the same order as it appeared in the file.
	postDataFrame$type <- as.character( postDataFrame$type )
	postDataFrame$type <- factor( postDataFrame$type,
	levels = unique( postDataFrame$type ) )

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

	print( "Post Data Frame Results:" )
	print( postDataFrame )

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

	requiredColumns <- c( "deltoconfrm", "elapsedel" )

	tryCatch( delAvgs <- 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 )
	}
	)


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

	delDataFrame <- melt( delAvgs )
	delDataFrame$scale <- fileData$scale
	delDataFrame$date <- fileData$date
	delDataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )

	colnames( delDataFrame ) <- c( "ms",
	"type",
	"scale",
	"date",
	"iterative" )

	# Format data frame so that the data is in the same order as it appeared in the file.
	delDataFrame$type <- as.character( delDataFrame$type )
	delDataFrame$type <- factor( delDataFrame$type,
	levels = unique( delDataFrame$type ) )

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

	print( "Del Data Frame Results:" )
	print( delDataFrame )

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

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

	# ------------------------------------------
	# Initializing variables used in both graphs
	# ------------------------------------------

	print( "Initializing variables used in both graphs." )

	defaultTextSize()
	xLabel <- xlab( "Build Date" )
	yLabel <- ylab( "Latency (ms)" )
	fillLabel <- labs( fill="Type" )

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

	wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )

	barWidth <- 0.3

	theme <- graphTheme()

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

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

	print( "Creating main plot for Post graph." )

	mainPlot <- ggplot( data = postDataFrame, aes( x = iterative,
	y = ms,
	fill = type ) )

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

	print( "Generating fundamental graph data for Post graph." )

	xScaleConfig <- scale_x_continuous( breaks = postDataFrame$iterative,
	label = postDataFrame$date )

	title <- labs( title = postChartTitle, subtitle = lastUpdatedLabel() )

	fundamentalGraphData <- mainPlot +
	xScaleConfig +
	xLabel +
	yLabel +
	fillLabel +
	theme +
	wrapLegend +
	colors +
	title

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

	print( "Generating bar graph for Post graph." )

	sum <- fileData[ 'posttoconfrm' ] +
	fileData[ 'elapsepost' ]

	values <- geom_text( aes( x = postDataFrame$iterative,
	y = sum + 0.03 * max( sum ),
	label = format( sum,
	digits = 3,
	big.mark = ",",
	scientific = FALSE ) ),
	size = 7.0,
	fontface = "bold" )

	result <- fundamentalGraphData +
	barGraphFormat +
	values

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

	saveGraph( postOutputFile )

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

	print( "Creating main plot for Del graph." )

	mainPlot <- ggplot( data = delDataFrame, aes( x = iterative,
	y = ms,
	fill = type ) )

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

	print( "Generating fundamental graph data for Del graph." )

	xScaleConfig <- scale_x_continuous( breaks = delDataFrame$iterative,
	label = delDataFrame$date )

	title <- labs( title = delChartTitle, subtitle = lastUpdatedLabel() )

	fundamentalGraphData <- mainPlot +
	xScaleConfig +
	xLabel +
	yLabel +
	fillLabel +
	theme +
	wrapLegend +
	colors +
	title

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

	print( "Generating bar graph for Del graph." )

	sum <- fileData[ 'deltoconfrm' ] +
	fileData[ 'elapsedel' ]

	values <- geom_text( aes( x = delDataFrame$iterative,
	y = sum + 0.03 * max( sum ),
	label = format( sum,
	digits = 3,
	big.mark = ",",
	scientific = FALSE ) ),
	size = 7.0,
	fontface = "bold" )

	result <- fundamentalGraphData +
	barGraphFormat +
	title +
	values

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

	saveGraph( delOutputFile )
	quit( status = 0 )