基于RHadoop的linear-least-squares算法

library(rmr2)## @knitr LLS-dataX = matrix(rnorm(2000), ncol = 10)X.index = to.dfs(cbind(1:nrow(X), X))y = as.matrix(rnorm(200))## @knitr LLS-sumSum =   function(., YY)     keyval(1, list(Reduce('+', YY)))## @knitr LLS-XtXXtX =   values(    from.dfs(      mapreduce(        input = X.index,        map =           function(., Xi) {            Xi = Xi[,-1]            keyval(1, list(t(Xi) %*% Xi))},        reduce = Sum,        combine = TRUE)))[[1]]## @knitr LLS-XtyXty =   values(    from.dfs(      mapreduce(        input = X.index,        map = function(., Xi) {          yi = y[Xi[,1],]          Xi = Xi[,-1]          keyval(1, list(t(Xi) %*% yi))},        reduce = Sum,        combine = TRUE)))[[1]]## @knitr LLS-solvesolve(XtX, Xty)## @knitr end