similar to: Hand-crafting an .RData file

Dear R friends. After having some troubles learning how to create a ffdf object, now I find myself having problems saving it. this is the data i´d like to save: str(DATA) List of 3 $ virtual: 'data.frame': 6 obs. of 7 variables: .. $ VirtualVmode : chr "double" "short" "integer" "integer" ... .. $ AsIs : logi FALSE FALSE FALSE

Hi, The read.csv.ffdf function in package ff will create the ff object physical file in the default directories, I am trying to let the files created in the paths users specify, I think the point is to make use of the asffdf_args parameter, I have a test CSV file named D:\rtemp\fftest.csv, the content of the file is as following: col1,col2,col3 1,"amber",2.4 2,"linda",4.5

I'm having trouble getting ffdfindexget to work right in Windows. Even the most trivial of examples gives me problems. > myVec = ff(1:5) > another = ff(10:14) > littleFrame = ffdf(myVec, another) > posVec = ff(c(2, 4), vmode = 'integer') > ffdfindexget(littleFrame, posVec) Error in if (any(B < 1)) stop("B too small") : missing value where TRUE/FALSE

Hi, I have two questions on using the ff package and wonder if anyone who used ff can share some thoughts. I need to save a matrix as a memory-mapped file and load it back later. To save the matrix, I use mat = matrix(1:20, 4, 5) matFF = ff(mat, dim=dim(mat), filename="~/a.mat", overwrite=TRUE, dimnames = dimnames(mat)) To load it back, I use matFF2 = ff(vmode = "double",

Hi, I am running the examples in page 70 of the ff package document, but it failed with the following error > cat("let's create some ff objects\n") let's create some ff objects > n <- 8e3 > a <- ff(sample(n, n, TRUE), vmode="integer", length=n, filename="d:/tmp/a.ff") > b <- ff(sample(255, n, TRUE), vmode="ubyte", length=n,

*Dear R users, Ive just started using the ff package. There is a csv file (~4Gb) with 7 columns and 6e+7 rows. I want to read only column from the file, skipping the first 100 rows. Below Ive provided different outcomes, which will clarify my problem * > sessionInfo() R version 2.14.2 (2012-02-29) Platform: x86_64-pc-mingw32/x64 (64-bit) locale: ... attached base packages: [1] tools

I've spent some time trying to wrap my head around reading in large csv files with the ff-package. I think I know how to do it, but am bumping into some problems. I've tried to recreate the issues as best as I can with a smaller example and maybe someone can help explain the problems. The following code just creates a csv file with an integer column, character column and logical column.

Hello to everyone. I'm trying to use the %in% to match to vectors in ff format. a<-as.ff(data[,1]) %in% fire$fecha > aff (open) logical length=3653 (3653) [1] [2] [3] [4] [5] [6] [7] [8] [3646] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE : FALSE [3647] [3648] [3649] [3650] [3651] [3652] [3653] FALSE FALSE FALSE FALSE FALSE FALSE

Dear list, I am trying to understand and use the ff package. As I had some problems saving some ff objects, and as I did not fully manage to understand the whole concept of *.ff, *.ffData and *.RData with the help of the documentation, I tried to reproduce the examples from the help of ffsave. When I ran, however : (copied from the help) message("let's create some ff objects")

Hello everyone, I need to create and work with some big matrices that actually have somewhat over 2 million columns and 117 rows. To do some calculations on such big matrices R just needs too much memory for my PC (4GB installed). So I need a solution to work with large datasets. I'm trying to use the ff-package but I don't think I really understand the whole functionality of the

I'm trying to import a table into R the file is about 700MB. Here's my first try: > DD<-read.table("01uklicsam-20070301.dat",header=TRUE) Error: cannot allocate vector of size 15.6 Mb In addition: Warning messages: 1: In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : Reached total allocation of 1535Mb: see help(memory.size) 2: In scan(file, what,

Hi, I am using version 2.1-1 of the ff package. I have a data set with 80 million rows and I need to create a new ffdf object, subseting by values in one of the original ffdf's columns. Here is my code: bigData <- read.table.ffdf(file="/data/demodata/data/smallData.txt", next.rows=1e5, head=TRUE, sep="|") dim(bigData) N <- nrow(bigData);N select <- ff(

Greetings useRs, Can anyone provide an example how to use ff to feed a very large data frame to glm? The data.frame cannot be loaded in R using conventional read.csv as it is too big. glm(...,data=ff.file) ?? Thank you Stephen B

Dear Experienced R Practitioners, I have 4GB .txt data called "dataset.txt" and have attempted to use *ff, bigmemory, filehash and sqldf *packages to import it, but have had no success. The readLines output of this data is: readLines("dataset.txt",n=20) [1] " "

Hi everyone, my apologies if I'm overlooking something obvious in the documentation. I'm relatively inexperienced with the (awesome) ff package. My goal is to use the read.table.ffdf() function to call the read.fwf() function and pass through the colClasses and comment.char arguments. The code below shows exactly what doesn't work for me. If the colClasses and comment.char

I've noticed that ff uses the unzip utility available on it's host OS to load datasets via ffload. It seems to work fine in linux, but when I try to use the package in Windows (hence dling Windows unzip utils) I get 2 errors, one telling me that the options aren't being passed to unzip correctly and another indicating that my filename is incorrect. First, does anyone know of an unzip

I'm comparing R-1.3.0 on Solaris 2.6 to R-1.3.1 on WindowsNT. The following 5-line script returns TRUE on Unix but FALSE on NT: fnam <- tempfile() file.create(fnam) txt <- paste("file.exists(\"", fnam, "\")", sep="") expr <- parse(text=txt) eval(expr) The issue seems to be that backslashes get lost in the parsing. A workaround is to change

Hi, I have been using ffsave.image() to save mixture of ff and normal objects in my workspace. e.g. ffsave.image(file = "C:\output\saveobjects", rootpath = "D:\fftempdir", safe = TRUE) It works fine but once my workspace has large (~4GB) objects, I get the error: Error in ffsave.image(file = "C:\output\savedobjects", rootpath = "D:\fftempdir", safe =

Really old subject?, so, all my apologizes for digging up but, since I also ran into this? maybe this hack can be useful to someone I propose monkey patching here: library(ff) my.as.ffdf.data.frame <- function (x, vmode = NULL, col_args = list(), ...) { rnam <- attr(x, "row.names") if (is.integer(rnam)) { if (all(rnam == seq_along(rnam))) rnam <- NULL else

Hi, I have 35 data files for reading. I would like get a program for performing reading of 35 files at once. All are of the type: Dados1.raw, Dados2.raw and so on. If the files have the same number of columns, I can read with the following commands: rm(list=ls()) filenames = list.files(path="~/Silvano/Arq", pattern="Dados+.*raw") names = substr(filenames, 1, 7) for(i in