I'm using ff and ffbase libraries to manage a big csv file (~40Go and 275e6 observations). I'd like to split/partition this file according to one of its columns (which is a factor column).
With a normal data frame, I would do something like that:
a <- data.frame(rnorm(10000,0,1),
sample(1:100,10000,replace=T),
sample(letters,10000,replace = T))
names(a) <- c('V1','V2','V3')
a_partition <- split(a,a$V3)
names(a_partition) <- paste("df",names(a_partition),sep = "_")
list2env(a_partition,globalenv())
but ff and ffbase doesn't have a split function. So, looking in the ffbase documentation, I found ffdfply and tried to use it as follows:
ffa <- as.ffdf(a)
ffa_partititon <- ffdfdply(x = ffa,split = ffa$V3)
Alas, I get the log message :
calculating split sizes
building up split locations
working on split 1/1, extracting data in RAM of 26 split elements,
totalling, 0.00015 GB, while max specified
data specified using BATCHBYTES is 0.01999 GB
... applying FUN to selected data
Error: argument "FUN" is missing, with no default
I tried FUN = as.data.frame (since the result of the function must be a data frame) with no luck : doing so makes ffa_partition a copy of ffa...
How can I partition my ffdf?
Two years late, but I believe this does what you needed:
result_list <- list()
for(letter in letters){
result_list[[letter]] <- subset(ffa, V3 == letter)
}