I have 2 relatively large data frames in R. I'm attempting to merge / find all combos, as efficiently as possible. The resulting df turns out to be huge (the length is dim(myDF1)[1]*dim(myDF2)[1]), so I'm attempting to implement a solution using ff. I'm also open to using other solutions, such as the bigmemory package to work-around these memory issues. I'm have virtually no experience with either of these packages.
Working example - assume I'm working with some data frame that looks similar to USArrests:
library('ff')
library('ffbase')
myNames <- USArrests
myNames$States <- rownames(myNames)
rownames(myNames) <- NULL
Now, I will fabricate 2 data frames, which represent some particular sets of observations from myNames. I'm going to try to reference them by their rownames later.
myDF1 <- as.ffdf(as.data.frame(matrix(as.integer(rownames(myNames))[floor(runif(3*1e5, 1, 50))], ncol = 3)))
myDF2 <- as.ffdf(as.data.frame(matrix(as.integer(rownames(myNames))[floor(runif(2*1e5, 1, 50))], ncol = 2)))
# unique combos:
myDF1 <- unique(myDF1)
myDF2 <- unique(myDF2)
For example, my first set of states in myDF1 are myNames[unlist(myDF1[1, ]), ]. Then I will find all combos of myDF1 and myDF2 using ikey :
# create keys:
myDF1$key <- ikey(myDF1)
myDF2$key <- ikey(myDF2)
startTime <- Sys.time()
# Create some huge vectors:
myVector1 <- ffrep.int(myDF1$key, dim(myDF2)[1])
myVector2 <- ffrep.int(myDF2$key, dim(myDF1)[1])
# This takes about 25 seconds on my machine:
print(Sys.time() - startTime)
# Sort one DF (to later combine with the other):
myVector2 <- ffsorted(myVector2)
# Sorting takes an additional 2.5 minutes:
print(Sys.time() - startTime)
1) Is there a faster way to sort this?
# finally, find all combinations:
myDF <- as.ffdf(myVector1, myVector2)
# Very fast:
print(Sys.time() - startTime)
2) Is there an alternative to this type of combination (without using RAM)?
Finally, I'd like to be able to reference any of the original data by row / column. Specifically, I'd like to get different types of rowSums. For example:
# Here are the row numbers (from myNames) for the top 6 sets of States:
this <- cbind(myDF1[myDF[1:6,1], -4], myDF2[myDF[1:6,2], -3])
this
# Then, the original data for the first set of States is:
myNames[unlist(this[1,]),]
# Suppose I want to get the sum of the Urban Population for every row, such as the first:
sum(myNames[unlist(this[1,]),]$UrbanPop)
3) Ultimately, I'd like a vector with the above rowSum, so I can perform some type of subset on myDF. Any advice on how to most efficiently accomplish this?
Thanks!
It's pretty much unclear to me what you intent to do with the rowSum and your 3) element but if you want an efficient and RAM-friendly combination of 2 ff vectors, to get all combinations, you can use expand.ffgrid from ffbase. The following will generate your ffdf with dimensions 160Mio rows x 2 columns in a few seconds.
require(ffbase)
x <- expand.ffgrid(myDF1$key, myDF2$key)