search for: n_max

..."Es_Ultima" = "c", "Comentarios" = "c"), locale = default_locale(), na = c("", " "), quoted_na = TRUE, quote = "\"", comment = "", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), progress = FALSE)) } # C.2) parallel Package: Environment Settings no_cores <- detectCores() c1 <- makeCluster(no_cores) invisible(clusterEvalQ(c1, library(readr))) setDefaultCluster(c1) # C.3) parRapply Function Application...

Hi Dave, That's rather frustrating. I've found vroom (from the package vroom) to be helpful with large files like this. Does the following give you any better luck? vroom(file_name, delim = ",", skip = 2459465, n_max = 5) Of course, when you know you've got errors & the files are big like that it can take a bit of work resolving things. The command line tools awk & sed might even be a good plan for finding lines that have errors & figuring out a fix, but I certainly don't envy you. All the...

...on.au at gmail.com> wrote: > Hi Dave, > > That's rather frustrating. I've found vroom (from the package vroom) to be > helpful with large files like this. > > Does the following give you any better luck? > > vroom(file_name, delim = ",", skip = 2459465, n_max = 5) > > Of course, when you know you've got errors & the files are big like that it > can take a bit of work resolving things. The command line tools awk & sed > might even be a good plan for finding lines that have errors & figuring out > a fix, but I certainly don&...

...09:18, Stevie Pederson wrote: > Hi Dave, > > That's rather frustrating. I've found vroom (from the package vroom) > to be helpful with large files like this. > > Does the following give you any better luck? > > vroom(file_name, delim = ",", skip = 2459465, n_max = 5) > > Of course, when you know you've got errors & the files are big like > that it can take a bit of work resolving things. The command line > tools awk & sed might even be a good plan for finding lines that have > errors & figuring out a fix, but I certainly d...

Greetings, I have a csv file of 76 fields and about 4 million records. I know that some of the records have errors - unmatched quotes, specifically.? Reading the file with readLines and parsing the lines with read.csv(text = ...) is really slow. I know that the first 2459465 records are good. So I try this: > startTime <- Sys.time() > first_records <- read.csv(file_name, nrows

Hi Andi, This is a set of updates for the firstfloor patch queue. Quick rundown: revert-mm-x86_64-mm-account-for-module-percpu-space-separately-from-kernel-percpu.patch separate-module-percpu-space.patch Update the module percpu accounting patch fix-ff-allow-percpu-variables-to-be-page-aligned.patch Make sure the percpu memory allocation is page-aligned

Hi Andi, This is a set of updates for the firstfloor patch queue. Quick rundown: revert-mm-x86_64-mm-account-for-module-percpu-space-separately-from-kernel-percpu.patch separate-module-percpu-space.patch Update the module percpu accounting patch fix-ff-allow-percpu-variables-to-be-page-aligned.patch Make sure the percpu memory allocation is page-aligned