應用程式效能分析
資料結構：
統計分析圖表：
Call: lm(formula = TXN_TIME ~ TXN_NO) Residuals: Min 1Q Median 3Q Max -0.12534 -0.05211 0.00262 0.04614 0.32040 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 6.138e-01 2.889e-01 2.125 0.0433 * TXN_NO -7.113e-07 2.533e-03 0.000 0.9998 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.09075 on 26 degrees of freedom Multiple R-squared: 3.034e-09, Adjusted R-squared: -0.03846 F-statistic: 7.888e-08 on 1 and 26 DF, p-value: 0.9998
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() } 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_DAY FROM "
, mySQL.Schema,
".reportdb ORDER BY DATE_DAY LIMIT 30", sep="") mySQL.DATA <- GetDB(mySQL.SQL) Date.Start <- mySQL.DATA$DATE_DAY[1] Date.End <- mySQL.DATA$DATE_DAY[length(mySQL.DATA$DATE_DAY)] mySQL.SQL <- paste("SELECT TO_DAYS(DATE_DAY) AS TXN_DATE, AVG(TXNNO) AS AVG_TXNNO, AVG(AVGTIME) AS AVG_TXNTIME FROM ",
mySQL.Schema,
".reportdb WHERE DATE_DAY BETWEEN '", Date.Start, "' AND '", Date.End,
"' GROUP BY DATE_DAY ORDER BY DATE_DAY", sep="") mySQL.DATA <- GetDB(mySQL.SQL) TXN_NO <- (mySQL.DATA$AVG_TXNNO) / 1000 TXN_TIME <- (mySQL.DATA$AVG_TXNTIME) TXN_DATE <- (mySQL.DATA$TXN_DATE) mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_TXN.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, TXN_NO~TXN_DATE, "TXN.NO~TXN.DATE (Last 30 Days)", "Day #", "TXN.NO (x1000)") mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_RESPONSE_TIME.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, TXN_TIME~TXN_DATE,
"TXN.RESPONSE_TIME~TXN.DATE (Last 30 Days)", "Day #", "TXN.RESPONSE.TIME") mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_TXN_TIME.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, TXN_TIME~TXN_NO,
"TXN.RESPONSE_TIME~TXN.NO (Last 30 Days)", "TXN.NO (x1000)", "TXN.RESPONSE.TIME") sink(paste(R.Analysis.Folder, "/", "AVG_TXN_TIME.txt", sep="")) summary(lm(TXN_TIME~TXN_NO)) sink() mySQL.SQL <- paste("SELECT APSVR, TO_DAYS(DATE_DAY) AS TXN_DATE, AVG(TXNNO) AS AVG_TXNNO, AVG(AVGTIME) AS AVG_TXNTIME FROM ",
mySQL.Schema, ".reportdb WHERE DATE_DAY BETWEEN '", Date.Start, "' AND '", Date.End,
"' GROUP BY APSVR, DATE_DAY ORDER BY APSVR, DATE_DAY", sep="") mySQL.DATA <- GetDB(mySQL.SQL) APPSVR <- (mySQL.DATA$APSVR) TXN_NO <- (mySQL.DATA$AVG_TXNNO) / 1000 TXN_TIME <- (mySQL.DATA$AVG_TXNTIME) TXN_DATE <- (mySQL.DATA$TXN_DATE) mySQL.Chart <- paste(R.Chart.Folder, "/", "AVG_SVR_TXN.png", sep="") SaveScatterPlotGraphics(mySQL.Chart, TXN_NO~TXN_DATE | APPSVR,
"TXN.NO~TXN.DATE by APPSVR (Last 30 Days)", "Day #", "TXN.NO (x1000)") rm(list=(ls()))