[分享] Strategies to Speedup R Code

[celestialgod (天)]

[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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推 andrew43: 好文！
推 cywhale: 看R-blogger讀到當下就聯想到C大諸多測快文~~
推 cywhale: Scaling data.table using index http://wp.me/pMm6L-tZA
→ cywhale: Solve R efficiently by data.table https://t.co/jmyUg