CPU 使用率分析
資料結構：
統計分析圖表：
ANOVA(CPU_USER) Tables of means Grand mean 33.65927 factor(HOSTNAME) F12APDB1 F12APDB2 61.7 0.013 rep 18.0 15.000 ANOVA(CPU_WAIT) Tables of means Grand mean 1.875587 factor(HOSTNAME) F12APDB1 F12APDB2 3.44 0.00103 rep 18.00 15.00000 ANOVA(CPU_SYS) Tables of means Grand mean 3.274888 factor(HOSTNAME) F12APDB1 F12APDB2 5.91 0.11 rep 18.00 15.00
GNU-R：
library(DBI) library(RMySQL) library(car) GetDB <- function (SQL) { mySQL.Connection <- dbConnect(MySQL(), host=mySQL.Host, user=mySQL.User, password=mySQL.Password, db=mySQL.Schema) ResultSet <- dbGetQuery(mySQL.Connection, SQL) dbDisconnect(mySQL.Connection) ResultSet } SaveScatterPlotGraphics <- function(pngFileName, formula, graphicsTitle, graphicsXTitle, graphicsYTitle) { png(file=pngFileName) scatterplot(formula, reg.line=lm, smooth=TRUE, spread=TRUE, boxplots='xy', span=0.5, main=graphicsTitle, xlab=graphicsXTitle, ylab=graphicsYTitle) dev.off() } PrintANOVA <- function (formula, heading) { cat(paste("ANOVA(", heading, ")", sep="")) cat("\n") R.ANOVA.CPU_USER = aov(formula) summary(R.ANOVA.CPU_USER) print(model.tables(R.ANOVA.CPU_USER, "means"), digits=3) cat("\n\n") } mySQL.Host <- "127.0.0.1" mySQL.User <- "nmon" mySQL.Password <- "nmon" mySQL.Schema <- "nmon" R.Chart.Folder <- "/var/nmon/Results/Graphics" R.Analysis.Folder <- "/var/nmon/Results/Analysis" mySQL.SQL <- paste("SELECT DISTINCT DATE(ZZZZ) AS TXN_DATE FROM ", mySQL.Schema, ".cpu_all ORDER BY ZZZZ LIMIT 30", sep="") mySQL.DATA <- GetDB(mySQL.SQL) Date.Start <- mySQL.DATA$TXN_DATE[1] Date.End <- mySQL.DATA$TXN_DATE[length(mySQL.DATA$TXN_DATE)] mySQL.SQL <- paste("SELECT HOSTNAME, TO_DAYS(DATE(ZZZZ)) AS TXN_DATE,
AVG(USER_PCT) AS CPU_USER, AVG(SYS_PCT) AS CPU_SYS, AVG(WAIT_PCT) AS CPU_WAIT FROM ", mySQL.Schema, ".cpu_all WHERE DATE(ZZZZ) BETWEEN '", Date.Start, "' AND '", Date.End, "' GROUP BY HOSTNAME, DATE(ZZZZ) ORDER BY HOSTNAME, DATE(ZZZZ)", sep="") mySQL.DATA <- GetDB(mySQL.SQL) TXN_DATE <- (mySQL.DATA$TXN_DATE) HOSTNAME <- (mySQL.DATA$HOSTNAME) CPU_USER <- (mySQL.DATA$CPU_USER) CPU_WAIT <- (mySQL.DATA$CPU_WAIT) CPU_SYS <- (mySQL.DATA$CPU_SYS) mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_HOST_CPU_USER.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, CPU_USER~TXN_DATE | HOSTNAME, "CPU.USER~TXN.DATE by HOST (Last 30 Days)", "Day #", "CPU%") mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_HOST_CPU_WAIT.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, CPU_WAIT~TXN_DATE | HOSTNAME, "CPU.WAIT~TXN.DATE by HOST (Last 30 Days)", "Day #", "CPU%") mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_HOST_CPU_SYS.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, CPU_SYS~TXN_DATE | HOSTNAME, "CPU.SYS~TXN.DATE by HOST (Last 30 Days)", "Day #", "CPU%") sink(paste(R.Analysis.Folder, "/", "AVG_HOST_CPU.txt", sep="")) PrintANOVA(CPU_USER~factor(HOSTNAME), "CPU_USER") PrintANOVA(CPU_WAIT~factor(HOSTNAME), "CPU_WAIT") PrintANOVA(CPU_SYS~factor(HOSTNAME), "CPU_SYS") sink() rm(list=(ls()))