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The bigmemory Package: Handling Large Data Sets in R Using ...

JSS Journal of Statistical Software MMMMMM YYYY, Volume VV, Issue II. The R Package bigmemory : Supporting Efficient Computation and Concurrent Programming with Large Data Sets. John W. Emerson Michael J. Kane Yale University Yale University Abstract Multi-gigabyte data sets challenge and frustrate R users even on well-equipped hard- ware. C/C++ and Fortran programming can be helpful, but is cumbersome for interactive data analysis and lacks the flexibility and power of R's rich statistical programming envi- ronment. The new package bigmemory bridges this gap, implementing massive matrices in memory (managed in R but implemented in C++) and supporting their basic manipu- lation and exploration. It is ideal for problems involving the analysis in R of manageable subsets of the data, or when an analysis is conducted mostly in C++.

> summary(x) min max mean NAs movie 1 17770 9.100050e+03 0 customer 1 480189 1.297173e+05 0 rating 1 5 3.603304e+00 0 year 1999 2005 2.004245e+03 0 month 1 12 6.692275e+00 0 There are, in fact, 17770 movies in the Netflix data and 480,189 customers. Ratings range from 1 to 5 for rentals in 1999 through 2005. Standard R matrix notation is ...

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