On 29/03/2014 09:28, peter dalgaard wrote:
On 28 Mar 2014, at 17:39 , T Bal wrote:
Hi,
After loading my data in R I get the error:
Error in .jcall("com/github/egonw/rrdf/RJenaHelper",
"Lcom/hp/hpl/jena/rdf/model/Model;", :
java.lang.OutOfMemoryError: GC overhead limit exceeded
How can I
On 28 Mar 2014, at 17:39 , T Bal wrote:
> Hi,
> After loading my data in R I get the error:
>
> Error in .jcall("com/github/egonw/rrdf/RJenaHelper",
> "Lcom/hp/hpl/jena/rdf/model/Model;", :
> java.lang.OutOfMemoryError: GC overhead limit exceeded
>
> How can I solve it?
For problems within
Hi,
After loading my data in R I get the error:
Error in .jcall("com/github/egonw/rrdf/RJenaHelper",
"Lcom/hp/hpl/jena/rdf/model/Model;", :
java.lang.OutOfMemoryError: GC overhead limit exceeded
How can I solve it?
[[alternative HTML version deleted]]
On Fri, 2013-12-27 at 16:47 -0600, Hadley Wickham wrote:
> For your original case, you may find it more useful to do memory +
> line profiling (e.g. as visualised by
> https://github.com/hadley/lineprof) to figure out what's going on.
>
> Hadley
I've been trying memory and line profiling, but mem
Hi Ross,
It's not obvious how useful memory.profile() is here. I created the
following little experiment to help me understand what
memory.profile() is showing (and to make it easier to see the
changes), but it's left me more confused than enlightened:
m_delta <- function(expr) {
# Evaluate in
I am trying to understand why a function causes my memory use to
explode. While doing that I noticed that my memory use as reported by
gc() is growing, but the results of memory.profile() are almost
unchanged (the count for raw grew by 3). How can the two functions
produce different results, and
Folks,
I have some computations in a function that create some large matrices.
I have been in the habit in these circumstances to call "null out" a matrix
once used and call gc().
Some pseudo code:
theFunction<-function(x, y, z, 1) {
myMatrix <- black.box.function(x, y, z, 100
On 09/10/2010 9:59 PM, Robin Jeffries wrote:
invisible(gc())
worked perfectly. Thanks Jeff.
@ Josh: I know how to toggle showing/hiding command echos, but I
haven't figured out how to toggle on/off any printed output.
Use "results=hide" as an Sweave option, e.g.
<>=
gc()
@
Duncan Murdoch
invisible(gc())
worked perfectly. Thanks Jeff.
@ Josh: I know how to toggle showing/hiding command echos, but I
haven't figured out how to toggle on/off any printed output.
On Sat, Oct 9, 2010 at 5:10 PM, Robin Jeffries wrote:
> I must be reading the help file for gc() wrong. I thought it sa
Try
invisible(gc())
?
"Robin Jeffries" wrote:
>I must be reading the help file for gc() wrong. I thought it said that
>gc(verbose=FALSE) will run the garbage collection without printing the
>Ncells/Vcells summary. However, this is what I get:
>
>gc(verbose = FALSE)
> used (Mb) gc trig
I must be reading the help file for gc() wrong. I thought it said that
gc(verbose=FALSE) will run the garbage collection without printing the
Ncells/Vcells summary. However, this is what I get:
gc(verbose = FALSE)
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 267097 14.3 531268 28
1) See ?"Memory-limits": it is almost certainly memory fragmentation.
You don't need to give the memory back to the OS (and few OSes actually do
so).
2) I've never seen this running a 64-bit version of R.
3) You can easily write a script to do this. Indeed, you could write an R
script to run m
On 4 February 2008 at 20:45, Doran, Harold wrote:
| I have a program which reads in a very large data set, performs some
analyses, and then repeats this process with another data set. As soon as the
first set of analyses are complete, I remove the very large object and clean up
to try and make
I have a program which reads in a very large data set, performs some analyses,
and then repeats this process with another data set. As soon as the first set
of analyses are complete, I remove the very large object and clean up to try
and make memory available in order to run the second set of an
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