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Dear R developers, While improving duplicated.array() and friends and developing equivalents for the new ff package for large datasets I came across two questions: 1) is it safe to use duplicated.default(), unique.default() and match() on arbitrary lists? If so, we can speed up duplicated.array and friends considerably by using list() instead of paste(collapse="\r") 2) while

I understand R is a "Pass-By-Value" language. I have a few practical questions, however. I'm dealing with a "large" dataset (~1GB) and so my understanding of the nuances of memory usage in R is becoming important. In an example such as: > d <- read.csv("file.csv"); > n <- apply(d, 1, sum); must "d" be copied to another location in memory in

Dear R community, ff Version 2.0 is available on CRAN. Based on paging concepts from version 1.0, 2.0 is a major redesign of this package for handling large datasets. We have implemented numerous enhancements and performance improvements to make this package suitable as a 'base' package for large data processing. The ff package provides atomic data structures that are stored on disk

Dear R community, ff Version 2.0 is available on CRAN. Based on paging concepts from version 1.0, 2.0 is a major redesign of this package for handling large datasets. We have implemented numerous enhancements and performance improvements to make this package suitable as a 'base' package for large data processing. The ff package provides atomic data structures that are stored on disk