knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(bigalgebra) library(bigmemory)
bigalgebra is designed to interoperate with the bigmemory ecosystem. This
vignette demonstrates how to create in-memory and file-backed big.matrix
objects, interact with them via the package's wrappers, and manage the
underlying resources safely.
big.matrix objectsIn-memory matrices behave much like ordinary R matrices but reside in shared memory, allowing multiple R sessions to access the same data.
X <- big.matrix(3, 3, type = "double", init = 0) X[,] <- matrix(1:9, nrow = 3) X[]
Once created, the objects can be passed directly to Level 1 helpers:
dvcal(ALPHA = 2, X = X, BETA = -1, Y = X) X[]
File-backed matrices persist their contents on disk, making them suitable for data sets that exceed available RAM.
dir.create(tmp_fb <- tempfile()) Y <- filebacked.big.matrix(4, 2, type = "double", backingpath = tmp_fb, backingfile = "fb.bin", descriptorfile = "fb.desc", init = 0) Y[,] <- matrix(runif(8), nrow = 4) Y[]
These objects participate in higher-level operations without being loaded into memory.
Z <- filebacked.big.matrix(4, 2, type = "double", backingpath = tmp_fb, backingfile = "res.bin", descriptorfile = "res.desc", init = 0) dvcal(ALPHA = 1.5, X = Y, BETA = 0, Y = Z) Z[]
The descriptor file records the metadata needed to reopen a file-backed matrix
in a new R session. The attach.big.matrix() helper reconstructs the object:
Y_desc <- dget(file.path(tmp_fb, "fb.desc")) Y_again <- attach.big.matrix(Y_desc) identical(Y[,], Y_again[,])
Any operations performed via bigalgebra update the shared backing file,
allowing all attached references to observe the change.
dsub(X = Z, Y = Y_again) Y_again[]
File-backed matrices allocate resources on disk. Deleting the backing and descriptor files once they are no longer needed helps keep the workspace tidy.
unlink(file.path(tmp_fb, c("fb.bin", "fb.desc", "res.bin", "res.desc"))) unlink(tmp_fb, recursive = TRUE)
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