[分享] Strategies to Speedup R Code
[關鍵字]: speedup R
[出處]:
http://www.r-bloggers.com/strategies-to-speedup-r-code/
[重點摘要]:
The for-loop in R, can be very slow in its raw un-optimised form, especially
when dealing with larger data sets. There are a number of ways you can make
your logics run fast, but you will be really surprised how fast you can
actually go.
This posts shows a number of approaches including simple tweaks to logic
design, parallel processing and Rcpp, increasing the speed by orders of
several magnitudes, so you can comfortably process data as large as 100
Million rows and more.
從簡入深介紹一些R加速的技巧，不少在板上都有被討論過
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R資料整理套件系列文：
magrittr #1LhSWhpH (R_Language) http://tinyurl.com/1LhSWhpH
data.table #1LhW7Tvj (R_Language) http://tinyurl.com/1LhW7Tvj
dplyr(上) #1LhpJCfB (R_Language) http://tinyurl.com/1LhpJCfB
dplyr(下) #1Lhw8b-s (R_Language)
tidyr #1Liqls1R (R_Language) http://tinyurl.com/1Liqls1R
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