similar to: Binding multiple data frames into single data frame

Hi all, I have R installed on a box, which is running on a machine with 16 core and Redhat - Linux. I am handling huge (size of dataset will be 5 GB) dataset. Lets assume that my data is in the form of structured (multiple) logs. I access the data by using all.files(). Since by default basic version of R utilizes single core, the processing of my analysis code is taking too much time. I got to

Hi all, I have the following sql query that I am executing on a machine with single core. I want to know how can I execute the same sqery on a maching that is running with 4 cores. Please provide me the code. NEW_TABLE <- rhive.query("SELECT A, B, COUNT(C) FROM TABLE_A WHERE A>='01-01-2012'") Also let me know how can I leverage only 2 / 3 cores of the machine.

Hi All, I want to join a table (Dataset) that is created in R with a table that is in oracle database. Can some one help me in accomplishing this task in R? Example Code: library(RODBC) DB_CONNECT <- odbcConnect("DSN_NAME") TABLE_JOIN <- sqlQuery(DB_CONNECT, "SELECT * FROM DB_TABLE WHERE COL_1 NOT IN (SELECT COL_1 FROM DATA_SET_R) ") Regards, Madana -- View this

Hi i have the data in the following format: rent,100,1,common,674 pipe,200,0,usual,864 car,300,1,uncommon,392:jump,700,0,common,664 car,200,1,uncommon,864:snap,900,1,usual,746 stint,600,1,uncommon,257 pull,800,0,usual,594 where as i want the above 6 lines data into 8 lines as below (Spliting row 3 & 4 at : and sending to a new row): rent,100,1,common,674 pipe,200,0,usual,864

On a Unix machine I ran caret::rfe using the multicore package, and I saved the resulting object using save(lm2, file = "lm2.RData"). [Reproducible example below.] When I try to load("lm2.RData") on my Windows laptop, I get Error in loadNamespace(name) : there is no package called 'multicore' I completely understand the error and I would like to ignore it and

Hi Friends, Kindly let me know whether is it possible to install R project in a Server (Remote) desktop, which can be accessed by many users by logging in with their credentials... Another concern is if i want to work with huge dataset (millions of records) what should be the system configuration? (currently i am getting an error : Cannot allocate vector of size 16.7 Mb) Regards, Madana -- View

Hi Friends, Currently i am using R-2.9.1. I am new to R and i am in learning stage. Can any one tell me whether R allows WAR file installation? Other concerns i have are: 1. Does R allows WAR file installation? 2. Does R has a web server or application server concept? 3. Can we create login credentials in R? Kindly clarify these things... Regards, Madana -- View this message in context:

dear r experts---Is there a multicore equivalent of by(), just like mclapply() is the multicore equivalent of lapply()? if not, is there a fast way to convert a data.table into a list based on a column that lapply and mclapply can consume? advice appreciated...as always. regards, /iaw ---- Ivo Welch (ivo.welch at gmail.com)

Hello all, I upgraded my R workstation, and to my dismay, only one core appears to be used during intensive computation of a bioconductor function. What I have now is two dual-core Xeon 5160 CPUs and 10 GB RAM. When I fully load it, top reports about 25% user, 75% idle and 0.98 short-term load. The archives gave nothing helpful besides mention of snow. I thought of posting to HPC, but this system

Sir, I want to apply mclapply() function for my analysis. So, I have to install multicore package. But I can not install the package. >install.packages("multicore") It gives that package multicore is not available. Can you help me? Regards, Suman Dhara [[alternative HTML version deleted]]

The attached code produces corrupted pdfs (test2.pdf, test4.pdf and test5.pdf). The resulting pdf depends on how many cores are available on the machine. I don't see why there should be any difference between the pdfs (exept for the timestamp). Doing many operations involving mclapply can increase the size of the resulting pdf by ten times! Thank you for checking this. require(multicore)

Dear all, I have an R script that uses Rcpp, and I have been trying to parallelize it using mclapply (I tried with the multicore and the parallel library) Sometimes (not always, interestingly), the CPU use for each core drops, usually so that the total over all cores reaches 100%, i.e., as fast as if using just one single core fully. I tried my code directly from within emacs, and also using a

Thanks Simon, I will take note of the sensible default for core usage. I?m trying to achieve small scale parallelism, where tasks take 1-5 seconds and make fuller use of consumer hardware. Its not a HPC-worthy computation but even laptops these days come with 4 cores and I don?t see a reason to not make use of it. The goal for the current piece of code I?m working on is to bootstrap many

Is there any reason to expect a problem ? i'm running this script on the cluster down the hall: module load R/2.11.0 R library(multicore) fxx<-function(ll) runif(1) mclapply(1:10,fxx) i get: Error in fork() : Unable to fork. less /proc/cpuinfo yields: processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Xeon(R) CPU

This is a 'rather than re-invent the wheel' post. Has anyone out there re-written combn so that it can be parallelized - with multicore, snow, or otherwise? I have a job that requires large numbers of combinations, and rather than get all of the index values, then crank it through mclapply, I was wondering if there was a way to just do this natively within a function. Just curious.

Dear R developers, with the inclusion of the package "parallel" in the upcoming release of R, users and package developers are likely to make increasing usage of parallelization features. In part, these features rely on forking the R process. As ?mcfork points out, fork()ing in a GUI process is typically a bad idea. In RKWard, we "only" seem to have problems with signals

Hello Digvijoy, > Does your kernel have inbuilt support for Logical Volumes > ,because your ouptut shows VFS is unable to mount root ,which > means dm-mod and multidevice modules wasnt compiled into the kernel. Multi-device support is compiled into my DomU kernel, device-mapper is built as a module. But I don''t think this has something to do with my problem because

I'm running r 2. on a mac running 10.6.4 and a dual-core macbook pro. I'm having a funny time with multicore. When I run it with 2 cores, mclapply, R borks with the following error. The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec(). Break on __THE_PROCESS_HAS_FORKED_AND_YOU_CANNOT_USE_THIS_COREFOUNDATION_FUNCTIONALITY___YOU_MUST_EXEC__()

Hello, I spent a lot of a time on a weird bug, and I just managed to narrow it down. In parallel code (here with parallel::mclappy, but I got it doMC/multicore too), if the library(tcltk) is loaded, R hangs when trying to open a DB connection. I got the same behaviour on two different computers, one dual-core, and one 2 xeon quad-core. Here's the code: library(parallel) library(RSQLite)

Hi, I am getting the follwoing error while installing gsubfn_0.6-4.tar.gz library for R. R version is 2.15.1 and i am installing on Redhat linux version 2.6.18-238.9.1.el5 (mockbuild at x86-002.build.bos.redhat.com<mailto:mockbuild at x86-002.build.bos.redhat.com>) (gcc version 4.1.2 20080704 (Red Hat 4.1.2-50)) * installing to library ?/home/mapred/installables/R/library? * installing