similar to: Utilizing the internet module

I'm trying to efficiently allow conversion of R objects to PostgreSQL bytea (raw binary) datatype within PL/R for persistent storage in Postgres tables. I have found R_serialize() which looks like what I need, -- e.g. R_serialize(object, NULL, FALSE, NULL) -- except that it is marked attribute_hidden. Is there some other externally available interface that I can use? Thanks, Joe

Hi, sorry if this question is trivial or unclear, this is my first venture into mixed C/R programming (I am reasonably experienced in each separately). I am trying to write a serialization function for a format called typedbytes, which is used as an interchange format in Hadoop circles. Since I would need to serialize according to the internal R format many small R objects I looked at the c

Hi, I've been doing some tests using serialize() to a raw vector: df <- data.frame(runif(50e6,1,10)) ser <- serialize(df,NULL) In this example the data frame and the serialized raw vector occupy ~400MB each, for a total of ~800M. However the memory peak during serialize() is ~1.2GB: $ cat /proc/15155/status |grep Vm ... VmHWM: 1207792 kB VmRSS: 817272 kB We work with very

Presumably one could stream over the data twice, the first to get the size, without storing the data. Slower but more memory efficient, unless I'm missing something. Michael On Tue, Mar 17, 2015 at 2:03 PM, Simon Urbanek <simon.urbanek at r-project.org> wrote: > Jorge, > > what you propose is not possible because the size of the output is > unknown, that's why a

Dear all, I have a problem to build a package on Windows XP while there is no problem on Linux. The Makefile is something like: ########### LIBNAME=cts PKG_LIBS = $(LAPACK_LIBS) $(BLAS_LIBS) $(FLIBS) OBJS=file1.o ... file20.o -llapack -lblas $(LIBNAME)$(SHLIB_EXT): $(OBJS) $(SHLIB_LD) $(SHLIB_LDFLAGS) -o $@ $(OBJS) $(FLIBS) clean: @rm -f *.o *.$(SHLIB_EXT) realclean: clean

Dear helpers, I am trying to create a library which uses some Fortran source files and Lapack and Blas subroutines. The Fortran source files from the original author contain subroutines isamax.f, sgefa.f and sgesl.f, which are part of BLAS subroutines on my Linux computer, but maybe different (old) versions. So in addition to these subroutines, there are other Lapack and Blas subroutines

Sometimes I find it useful to put C or Fortran sources under subdirs of "mypackage/src", especially to distinguish between my own files and e.g. lapack or blas sources. To get this working I would need a Makefile in my package which contains the appropriate dependencies to these sources in subdirs. But I don't want to add a complete Makefile, I want only a Makevars file containing

Dear R developers, While improving duplicated.array() and friends and developing equivalents for the new ff package for large datasets I came across two questions: 1) is it safe to use duplicated.default(), unique.default() and match() on arbitrary lists? If so, we can speed up duplicated.array and friends considerably by using list() instead of paste(collapse="\r") 2) while

Hi, Similar questions have come up before on the list and elsewhere but I haven't found a solution yet. winbuilder's install.out shows data.table's .c files compiled with -O3 on Win32 but -O2 on Win64. The same happens on R-Forge. I gather that some packages don't work with -O3 so the default is -O2. I've tried this in data.table's Makevars (entire contents) : ====

Jorge, what you propose is not possible because the size of the output is unknown, that's why a dynamically growing PStream buffer is used - it cannot be pre-allocated. Cheers, Simon > On Mar 17, 2015, at 1:37 PM, Martinez de Salinas, Jorge <jorge.martinez-de-salinas at hp.com> wrote: > > Hi, > > I've been doing some tests using serialize() to a raw vector: >

Hi, I've been doing some tests using serialize() to a raw vector: df <- data.frame(runif(50e6,1,10)) ser <- serialize(df,NULL) In this example the data frame and the serialized raw vector occupy ~400MB each, for a total of ~800M. However the memory peak during serialize() is ~1.2GB: $ cat /proc/15155/status |grep Vm ... VmHWM: 1207792 kB VmRSS: 817272 kB We work with very

Around line 527 of configure.ac in R-2.1.1 appears the following: darwin*) ## MacOS 10.3 and 10.4 do AM_CONDITIONAL(BUILD_DLFCN_DARWIN, false) ## SI says we want '-lcc_dynamic' on Darwin, although currently ## http://developer.apple.com /documentation/MacOSX/ has nothing ## official. AC_CHECK_LIB(cc_dynamic, main) ;; *)

In principle, yes (that's what Rserve serialization does), but AFAIR we don't have the infrastructure in place for that. But then you may as well serialize to a connection instead. To be honest I don't see why you would serialize anything big to a vector - you can't really do anything useful with that ... (what you couldn't do with the streaming version). Sent from my iPhone

I upgraded to R-2.2.1 on two PPC G5 computers today. Further I want to work with the tseries package for the first time. As root with R CMD INSTALL tseries_0.10-0.tar.gz I get the following gcc-3.3 -bundle -flat_namespace -undefined suppress -L/usr/local/lib - o tseries.so arma.o bdstest.o boot.o dsumsl.o garch.o ppsum.o tsutils.o -framework vecLib -L/usr/local/lib/gcc/powerpc-apple-

Hi, Li and all lists, More, I have searched the web, and found one solution as described in: https://stat.ethz.ch/pipermail/bioc-devel/2007-June/001168.html But, My condition is some how different: 1) my g++ version is: g++ (GCC) 3.2.2 20030222 (Red Hat Linux 3.2.2-5) 2) the SHLIB file is the same, but some difference in /usr/local/lib/R/etc/Makeconf: SHELL = /bin/sh SHLIB_CFLAGS =

I have a package that contains some fortran code. It has been built in the past, but now I have an updated Apple OSX 10.4 (Tiger) system, and it fails. The behaviour is as follows $ R CMD CHECK oce ,,, gcc-3.3 -bundle -flat_namespace -undefined suppress -L/usr/local/lib -o oce.so geoddist.o ocecp.o rho.o spice.o strho.o theta.o tsrho.o -

problem of the very large memory require by the Sign extension. --- R-2.5.0.orig/src/main/serialize.c 2007-03-27 01:42:08.000000000 +0900 +++ R-2.5.0/src/main/serialize.c 2007-06-25 00:48:58.000000000 +0900 @@ -1866,7 +1866,7 @@ static void resize_buffer(membuf_t mb, int needed) { - int newsize = 2 * needed; + size_t newsize = 2 * needed; mb->buf = realloc(mb->buf,

we are trying to adapt the configure in order to work with latest gcc3.3 (from apple) and g77 3.4 (from http://gravity.psu.edu/~khanna/hpc.html ) At the moment there is no need to define the __DEBUGGING__ but there is still a problem with the -lcc_dynamic does any of you know how to check for this library and explain why we see -lcc_dynamic often passed as an ld flag. Where to find doc on

Hello all, I set 'UDUNITS_PATH' and 'NETCDF_PATH' successfully to my custom places and then % R CMD INSTALL RNetCDF_1.1-3.tar.gz and got this: ... checking for executable suffix... checking for object suffix... o checking whether we are using the GNU C compiler... yes checking whether gcc accepts -g... yes checking for main in -lnetcdf... yes checking for main in -ludunits...

Is this possible? For instance, I have a function that returns a vector length 3. In one statement I'd like to assign each element of the vector to different variables. Syntactically, I hoped this would work: c(x,y,z) <- myfun(); Thanks, -- Jeffrey Horner Computer Systems Analyst School of Medicine 615-322-8606 Department of Biostatistics Vanderbilt University