R --vsize v --nsize n
v
|
Use v bytes of heap memory
|
n
|
Use n cons cells.
|
In these cases, you should restart R (after saving your current
workspace) with more memory available, using the command line
options --nsize and --vsize. To understand these
options, one needs to know that R maintains separate areas for fixed
and variable sized objects. The first of these is allocated as an
array of ``cons cells'' (Lisp programmers will know what they are,
others may think of them as the building blocks of the language
itself, parse trees, etc.), and the second are thrown on a
``heap''.
The --nsize option can be used to specify the
number of cons cells (each occupying 16 bytes) which R is to use
(the default is 250000), and the --vsize option to specify
the size of the vector heap in bytes (the default is 6 MB).
Both options must be integers or integers ending with
M, K, or k meaning Mega
(= 2^{20} = 1048576), (computer) Kilo (= 2^{10} = 1024),
or regular kilo (= 1000). (The minimum allowed values are
200000 and 2M.)
E.g., to read in a table of 10000 observations on 40 numeric
variables, R --vsize 10M should do; For
source()ing a large file, you'd use R --nsize 500k.
Note that the information on where to find vectors and strings on the heap is stored using cons cells. Thus, it may also be necessary to allocate more space for cons cells in order to perform computations with very ``large'' variable-size objects.
You can find out the current memory consumption (the proportion of
heap and cons cells used) by typing gc() at the R
prompt. This may help you in finding out whether to increase
--vsize or --nsize. Note that following
gcinfo(TRUE), automatic garbage collection always
prints memory use statistics.
R will tell you whether you ran out of cons or heap memory.
The defaults for --nsize and --vsize can be changed by
setting the environment variables R_NSIZE and R_VSIZE
respectively, perhaps most conveniently on Unix in the file
`~/.Renviron'.
When using read.table, the memory requirements are in
fact higher than anticipated, because the file is first read in as
one long string which is then split again. Use scan if
possible in case you run out of memory when reading in a large table.
gc for information on the garbage collector.# Start R with 15MB of heap memory and 1 million cons cells R --vsize 15M --nsize 1000k