按xdf文件分组?

这个 dplyrXdf package 允许您在xdf文件上执行这样的dplyr操作。

library(dplyrXdf)
src <- RxXdfData("src.xdf")
dest <- src %>%
    group_by(A, B, C) %>%
    summarise(sum=sum(D), min=min(D), max=max(D), mean=mean(D), sd=sd(D))

如果您想创建一个新的xdf文件,我建议使用“revopemar”库,该库包含在ML服务器中。如果您添加一个可重复的示例,那就更好了,但答案可能是这样的:

library(RevoPemaR)
byGroupPemaObj <- PemaByGroup()
groupVals <- pemaCompute(
pemaObj = byGroupPemaObj, 
data = "input.xdf",
outData = "output.xdf", 
groupByVar =  c("A", "B", "C"), 
computeVars = c("D"),
    fnList = list(
     sum= list(FUN = sum, x = NULL, na.rm = TRUE),
     min= list(FUN = min, x = NULL, na.rm = TRUE)
     max= list(FUN = max, x = NULL, na.rm = TRUE),
     mean= list(FUN = mean, x = NULL, na.rm = TRUE),
     sd = list(FUN = sd, x = NULL, na.rm = TRUE)
    )
)

但是你还有另一个选择,那就是RX摘要。对于每个变量:

rxSummary(D~F(A), 
    data = "input.xdf" ,
    byGroupOutFile = "out.xdf", 
    summaryStats = c( "Mean", "StdDev", "Min", "Max", "Sum")
)