Why does a 2 GB RData file exceed my 16GB memory limit when reading it in?

David,

If the ".Rdata" contains more than one object you could (and maybe should
use) the SOAR package (from Venables). This package helps you to split the
objects over multiple RData files. It's useful when you have numerous
medium-large objects in the workspace but doesn't use then at the same
time.

When use SOAR::Attach(), for instance, it loads the current name of all the
objects and retain than available in the searchpath but without load then
to the memory. As you call, they will be loaded into the memory.

If needed, you can update the object and then store it again with the
SOAR::Store()

For my use, this package is terrific! I use it with an analysis that I need
to repeat over medium-large similars datasets.

Best
Leandro

Em qua., 2 de set. de 2020 ?s 18:33, David Jones <david.tn.jones at gmail.com>
escreveu:

Thank you Uwe, John, and Bert - this is very helpful context.

If it helps inform the discussion, to address John and Bert's
questions - I actually had less memory free when I originally ran the
analyses and saved the workspace, than when I read in the data back in
later on (I rebooted in an attempt to free all possible memory before
rereading the workspace back in).



On Wed, Sep 2, 2020 at 1:27 PM John via R-help <r-help using
r-project.org> wrote:

On Wed, 2 Sep 2020 13:36:43 +0200
Uwe Ligges <ligges using statistik.tu-dortmund.de> wrote:

On 02.09.2020 04:44, David Jones wrote:

I ran a number of analyses in R and saved the workspace, which
resulted in a 2GB .RData file. When I try to read the file back
into R

Compressed in RData but uncompressed in main memory....

later, it won't read into R and provides the error: "Error: cannot
allocate vector of size 37 Kb"

This error comes after 1 minute of trying to read things in - I
presume a single vector sends it over the memory limit. But,
memory.limit() shows that I have access to a full 16gb of ram on my
machine (12 GB are free when I try to load the RData file).

But the data may need more....

gc() shows the following after I receive this error:

used (Mb) gc trigger (Mb) max used (Mb)
Ncells 623130 33.3 4134347 220.8 5715387 305.3
Vcells 1535682 11.8 883084810 6737.5 2100594002 16026.3

So 16GB were used when R gave up.

Best,
Uwe Ligges

For my own part, looking at the OP's question, it does seem curious
that R could write that .RData file, but on the same system not be able
to reload something it created.  How would that work.  Wouldn't the
memory limit have been exceeded BEFORE the the .RData file was written
the FIRST time?

JDougherty

R experts may give you a detailed explanation, but it is certainly

possible

that the memory available to R when it wrote the file was different than
when it tried to read it, is it not?

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

        [[alternative HTML version deleted]]