similar to: ffsave problems

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 R community, Package bit version 1.1-3 and ff version 2.1.2 is available on CRAN and should be useful to handle large datasets. It adds convenient utilities for managing ff objects and files (see ?ffsave) and removes some performance bottlenecks. In case you experience unexpected performance problems with ff, here is a couple of recommendations based on FAQs: 1) Compare the size of data

Dear R community, Package bit version 1.1-3 and ff version 2.1.2 is available on CRAN and should be useful to handle large datasets. It adds convenient utilities for managing ff objects and files (see ?ffsave) and removes some performance bottlenecks. In case you experience unexpected performance problems with ff, here is a couple of recommendations based on FAQs: 1) Compare the size of data

I use the ff-package for large data and have good success in session. To ensure my data is available for the next R session, I save my workspace and use the /ffsave/ command to archive my large data objects. Syntax is simple: > ffsave(file="~/path/archiveName", list="objectName") when I have multiple files to save, the list is expanded using c(). When I start a new R

Hi, I'm trying to introduce a (spatial) exponential correlation structure (with range=200 and nugget.effet of 0.3) in a lme model of this form: lme(ARBUS~YEAR, random=~1|IDSOUS). The structure of the data is "IDSOUS" "XMIN" "YMAX" "YEAR" "ARBUS" with 2 years of data and 5600 points for each year. I do:

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 =

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(

Dear R gurus, I am trying to overload some operators in order to let these work with the ff package by registering the S3 objects from the ff package and overloading the operators as shown below in a reproducible example where the "*" operator is overloaded. require(ff) setOldClass(Classes=c("ff_vector")) setMethod( f="*", signature = signature(e1 =

Hi All, My script generates a mixture of normal and ff objects. I need to run the script for different parameter settings. Very often I would like to save the workspace for each parameter setting, so that I can get back to it later on. Is there an easy way to do this, instead of needing to save individual ff objects separately? I've tried the naive way of just saving the workspace, only to

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")

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,

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

R-helpers: What would be the absolute fastest way to make a large "empty" file (e.g. filled with all zeroes) on disk, given a byte size and a given number number of empty values. I know I can use writeBin, but the "object" in this case may be far too large to store in main memory. I'm asking because I'm going to use this file in conjunction with mmap to do parallel

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

Hi all, I am having trouble loading a ff object previously saved in a different computer. I have both files .ffData and .RData, and the first of them is 13Mb large from which I know the data is therein. But when I try to ffload it, checkdir error: cannot create /home/_myUser_ Permission denied unable to process home/_myUser_/Rtempdir/ff1a831d500b8d.ff. and

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

Dear R Helpers, I would like to report on an error in the ff package here. The ff package is an R package which enables us to store large data on disk systematically and have fast access to the database. I used the package in Linux as a guest OS of VirtualBox, and executed the following commands. library(ff)

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",

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, I frequently have to export a large quantity of data from some source (for example, a database, or a hand-written perl script) and then read it into R. This occasionally takes a lot of time; I'm usually using read.table("filename",comment.char="",quote="") to read the data once it is written to disk. However, I *know* that the program that generates