如何在R中显示并行计算中代码的进度？

Question

我现在正在处理一个大型数据集，某些函数可能需要几个小时才能处理。我想知道如何通过进度条或数字（1,2,3,...,100）来显示代码的进度。我想将结果存储为包含两列的数据框。这是一个例子。谢谢

require(foreach)
require(doParallel)
require(Kendall)

cores=detectCores()
cl <- makeCluster(cores-1)
registerDoParallel(cl)

mydata=matrix(rnorm(8000*500),ncol = 500)
result=as.data.frame(matrix(nrow = 8000,ncol = 2))
pb <- txtProgressBar(min = 1, max = 8000, style = 3)

foreach(i=1:8000,.packages = "Kendall",.combine = rbind) %dopar%         
{
  abc=MannKendall(mydata[i,])
  result[i,1]=abc$tau
  result[i,2]=abc$sl
  setTxtProgressBar(pb, i)
}
close(pb)
stopCluster(cl)

但是，当我运行代码时，我没有看到任何进度条出现，结果不正确。有什么建议吗？谢谢

Answer 1

doSNOW 包支持进度条，而 doParallel 不支持。这是在您的示例中放置进度条的方法：

require(doSNOW)
require(Kendall)
cores <- parallel::detectCores()
cl <- makeSOCKcluster(cores)
registerDoSNOW(cl)
mydata <- matrix(rnorm(8000*500), ncol=500)
pb <- txtProgressBar(min=1, max=8000, style=3)
progress <- function(n) setTxtProgressBar(pb, n)
opts <- list(progress=progress)
result <- 
  foreach(i=1:8000, .packages="Kendall", .options.snow=opts,
          .combine='rbind') %dopar% {
    abc <- MannKendall(mydata[i,])
    data.frame(tau=abc$tau, sl=abc$sl)
  }
close(pb)
stopCluster(cl)

Answer 2

我认为 pbapply 包也能完成这项工作。

require(parallel)
require(pbapply)

mydata=matrix(rnorm(8000*500),ncol = 500)

cores=detectCores()
cl <- makeCluster(cores-1)
parallel::clusterExport(cl= cl,varlist = c("mydata"))
parallel::clusterEvalQ(cl= cl,library(Kendall))

result = pblapply(cl = cl,
         X = 1:8000,
         FUN = function(i){
  abc=MannKendall(mydata[i,])
  result = as.data.frame(matrix(nrow = 1,ncol = 2))
  result[1,1]=abc$tau
  result[1,2]=abc$sl
  return(result)
})

result = dplyr::bind_rows(result)
stopCluster(cl)

根据文档，如果套接字集群是通过 cl 提供的，那么它会调用 parLapply()

Parallel processing can be enabled through the cl argument. parLapply is called when cl is a ’cluster’ object, mclapply is called when cl is an integer.

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