Hello, Writing to seek help in regard to some unexpected performance anomaly i am observing in using tsoutlers:tso on the mac vs on an AWS cloud server.. I am running the following code with very small dataset of about 208 records. d.dir <- '/Users/darshanpandya/xxxxxx' FNAME <- 'my_data.csv' d.input <- fread(file.path(paste0(d.dir,"/zzz/"),FNAME,fsep .Platform$file.sep), header = TRUE, stringsAsFactors = FALSE, showProgress = TRUE) %>% as.data.frame d.input$dummy_date <- as.Date(d.input$dummy_date, "%Y-%m-%d") selectedCols <- c("observation","dummy_date") inputData <- d.input[,selectedCols] outlier.types <- list("Additive Outliers","Levels Shifts","Seasonal Level Shifts","Innovation Outlier","Temporary Change") tsFrequency <- 52 params <- list("outlier.types" = outlier.types,"tsFrequency" = tsFrequency) tsFrequency = params$tsFrequency outTypes <- unlist(params$outlier.types) ts.var <- ts(inputData[,1], frequency = tsFrequency) ts_outlier <- tso(ts.var, types ?outlier.types ? , maxit = 1) ? This piece of code runs in about 60 seconds on my laptop but take about upward of 13 mins on a decent AWS node with nothing else running on it. Any hints as to why this is happening is greatly appreciated. Thank you for your help. ? -- Sincerely, Darshan [[alternative HTML version deleted]]
Hello, Writing to seek help in regard to some unexpected performance anomaly i am observing in using tsoutlers:tso on the mac vs on an AWS cloud server.. I am running the following code with very small dataset of about 208 records. d.dir <- '/Users/darshanpandya/xxxxxx' FNAME <- 'my_data.csv' d.input <- fread(file.path(paste0(d.dir,"/zzz/"),FNAME,fsep .Platform$file.sep), header = TRUE, stringsAsFactors = FALSE, showProgress = TRUE) %>% as.data.frame d.input$dummy_date <- as.Date(d.input$dummy_date, "%Y-%m-%d") selectedCols <- c("observation","dummy_date") inputData <- d.input[,selectedCols] outlier.types <- list("Additive Outliers","Levels Shifts","Seasonal Level Shifts","Innovation Outlier","Temporary Change") tsFrequency <- 52 params <- list("outlier.types" = outlier.types,"tsFrequency" = tsFrequency) tsFrequency = params$tsFrequency outTypes <- unlist(params$outlier.types) ts.var <- ts(inputData[,1], frequency = tsFrequency) ts_outlier <- tso(ts.var, types ?outlier.types ? , maxit = 1) ? This piece of code runs in about 60 seconds on my laptop but take about upward of 13 mins on a decent AWS node with nothing else running on it. Any hints as to why this is happening is greatly appreciated. Thank you for your help. -- Sincerely, Darshan [[alternative HTML version deleted]]
You can record the time to evaluate each line by wrapping each line in a call to system.time(). E.g., expressions <- quote({ # paste your commands here, or put them into a file and use exprs <- parse("thatFile") d.dir <- '/Users/darshanpandya/xxxxxx' FNAME <- 'my_data.csv' d.input <- fread(file.path(paste0(d.dir,"/zzz/"),FNAME,fsep .Platform$file.sep), header = TRUE, stringsAsFactors = FALSE, showProgress = TRUE) %>% as.data.frame # ... the rest of your lines }) expressions <- as.list(expressions)[-1] timedExpressions <- lapply(expressions, function(expr)bquote(system.time(.(expr)))) source(exprs=timedExpressions, echo=TRUE) See which line (or lines) show big time differences on the two platforms. Bill Dunlap TIBCO Software wdunlap tibco.com On Fri, Apr 13, 2018 at 8:33 AM, Darshan Pandya <darshanpandya at gmail.com> wrote:> Hello, > > Writing to seek help in regard to some unexpected performance anomaly i am > observing in using tsoutlers:tso on the mac vs on an AWS cloud server.. > > > I am running the following code with very small dataset of about 208 > records. > > d.dir <- '/Users/darshanpandya/xxxxxx' > FNAME <- 'my_data.csv' > > d.input <- fread(file.path(paste0(d.dir,"/zzz/"),FNAME,fsep > .Platform$file.sep), header = TRUE, stringsAsFactors = FALSE, showProgress > = TRUE) %>% as.data.frame > d.input$dummy_date <- as.Date(d.input$dummy_date, "%Y-%m-%d") > > selectedCols <- c("observation","dummy_date") > inputData <- d.input[,selectedCols] > outlier.types <- list("Additive Outliers","Levels Shifts","Seasonal Level > Shifts","Innovation Outlier","Temporary Change") > tsFrequency <- 52 > params <- list("outlier.types" = outlier.types,"tsFrequency" = tsFrequency) > > tsFrequency = params$tsFrequency > outTypes <- unlist(params$outlier.types) > ts.var <- ts(inputData[,1], frequency = tsFrequency) > ts_outlier <- tso(ts.var, types > ?outlier.types ? > , maxit = 1) > > ? > > This piece of code runs in about 60 seconds on my laptop but take about > upward of 13 mins on a decent AWS node with nothing else running on it. > > Any hints as to why this is happening is greatly appreciated. > Thank you for your help. > > > > > > -- > Sincerely, > Darshan > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]