8.2 MapReduce

高阶函数，简单来说，就是参数为函数，返回值也是函数。Base R 提供了 Reduce 、Filter 、Find 、Map 、Negate 和 Position 等常用函数，此外还有 *apply 族。

与 purrr::map 比较

在 R 语言里玩转apply， Map() 和 Reduce()²¹，下面分别以提取合并多张 XLSX 表格²²，分组计算²³ 和子集操作 ²⁴ 为例，从函数式编程到 MapReduce ²⁵，制作数据透视表²⁶，用于数据处理的函数式编程和单元测试 Functional programming and unit testing for data munging with R 特别是第三章 https://b-rodrigues.github.io/fput/，然后是函数式编程与数据建模 Modeling data with functional programming in R²⁷

add <- function(x) Reduce("+", x)
add(list(1, 2, 3))

## [1] 6

add_accuml <- function(x) Reduce("+", x, accumulate = TRUE)
add_accuml(list(1, 2, 3))

## [1] 1 3 6

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21. https://stackoverflow.com/questions/3505701/grouping-functions-tapply-by-aggregate-and-the-apply-family↩︎

22. https://trinkerrstuff.wordpress.com/2018/02/14/easily-make-multi-tabbed-xlsx-files-with-openxlsx/↩︎

23. https://statcompute.wordpress.com/2018/09/03/playing-map-and-reduce-in-r-by-group-calculation/↩︎

24. https://statcompute.wordpress.com/2018/09/08/playing-map-and-reduce-in-r-subsetting/↩︎

25. https://cartesianfaith.com/2015/09/17/from-functional-programming-to-mapreduce-in-r/↩︎

26. https://digitheadslabnotebook.blogspot.com/2010/01/pivot-tables-in-r.html↩︎

27. https://cartesianfaith.files.wordpress.com/2015/12/rowe-modeling-data-with-functional-programming-in-r.pdf↩︎