Reputation: 42030
I'm trying to use big.matrix objects in my R code, but I'm having trouble saving them to a file using saveRDS
, which is how I normally save objects:
> library(bigmemory)
Loading required package: bigmemory.sri
Loading required package: BH
bigmemory >= 4.0 is a major revision since 3.1.2; please see packages
biganalytics and and bigtabulate and http://www.bigmemory.org for more information.
> x <- big.matrix(5, 2, type="integer", init=0,
+ dimnames=list(NULL, c("alpha", "beta")))
> saveRDS(x, "bigmem-test.RDS")
> y <- readRDS("bigmem-test.RDS")
> y
An object of class "big.matrix"
Slot "address":
<pointer: (nil)>
> print(y[])
*** caught segfault ***
address 0x51, cause 'memory not mapped'
Traceback:
1: .Call("GetMatrixAll", x@address)
2: GetAll.bm(x)
3: .local(x, ...)
4: y[]
5: y[]
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection: 3
I assume that saveRDS is somehow failing to realize that the big.matrix object is actually a pointer to some other memory, and is effectively just saving a pointer. Is there any way I can work around this?
(I don't really want to use a file-backed big.matrix object because the object I actually want to save is a complex data structure containing one or more big.matrix objects, so then I would need a backing file for each big.matrix contained in the object, and then the object would be serialized to an indeterminate number of files instead of just one.)
Upvotes: 2
Views: 1752
Reputation: 4686
You can try
> saveRDS(describe(x), "bigmem-test.RDS")
> y <- attach.big.matrix(readRDS("bigmem-test.RDS"))
I'm not sure what you intend to achieve though. The above will work within the same R session. But without file-backing, anything you have in memory will be gone after you end the R session and the above will not work because whatever it is pointing to will be gone.
Upvotes: 1
Reputation: 368301
But big.memory
objects sit behind an external pointer so that they outside the control of R. That means that you're idea of saving them as RDS objects from R is doomed from the start.
You could cast them to normal objects eating lots of memory and then write as RDS. Otherwise maybe look into filebased.bigmatrix()
?
Upvotes: 0