I�ve been reading in binary data collected via LabView for a project, and after
upgrading to R 3.5.0, the code returns an error indicating that the 'vector
memory is exhausted�. I�m happy to provide a sample binary file; even ones
that are quite small (12 MB) generate this error. (I wasn�t sure whether a
binary file attached to this email would trigger a spam filter.)
bin.read = file(files[i], "rb�)
datavals = readBin(bin.read, integer(), size = 2, n = 8*hertz*60*60000, endian
= "little�)
Error: vector memory exhausted (limit reached?)
sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6
This does not happen in R 3.4 (R version 3.4.4 (2018-03-15) -- "Someone to Lean
On�) - the vector is created and populated by the binary file values without
issue, even at a 1GB binary file size.
Other files that are read in as csv files, even at 1GB, load correctly to 3.5,
so I assume that this is a function of a vector being explicitly
defined/changed in some way from 3.4 to 3.5.
Any help, suggestions or workarounds are greatly appreciated!
Val
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