Displaying 1 result from an estimated 1 matches for "dataforcoln".
2009 Dec 14
1
as.data.frame requires a lot of memory (PR#14140)
...ibutes) the
conversion to a data frame requires has to be killed at with 60gb of
memory usage while it should only require 17.6gb (2*8.8gb).
dfn <- rep(list(rep(0, 4096)), 4096)
test <- as.data.frame.list(dfn)
I also tried the incremental construction of the
data-frame: df$colN <- dataForColN. While I currently can't say much
about the memory usage, it takes a looong time.
After the construction the saved-and-loaded data-frame has the expected size.
What is the recommended way to construct larger data-frames?