future example for parallel processing very raw

gistfile1.txt

library(microbenchmark)
library(tibble)
library(future)
library(dplyr)
nids <- 16
sleep_times <- data_frame(REP = 1:nids, sleep_time = round(runif(nids, 0, 2), 0))
sleep_times

eager_bm <- function(sleep_times) {
  plan(eager)
  f <- list()
  for (ii in 1:nrow(sleep_times)) {
       f[[ii]] <- future({
         message("a message inside an eager future")
         sleep_time <- slice(sleep_times, ii)[[2]]
         start_time <- Sys.time()
         Sys.sleep(sleep_time)
          list(sleep_time = sleep_time, 
               start_time = start_time,
               end_time = Sys.time(), 
               pid = Sys.getpid())
       })
   }
   v <- lapply(f, FUN = value)
  bind_rows(v)
}
multiprocess_bm <- function(sleep_times) {
  plan(multiprocess)
  f <- list()
  for (ii in 1:nrow(sleep_times)) {
    f[[ii]] <- future({
         message("a message inside a multiprocess future, you'll never see me")
      sleep_time <- slice(sleep_times, ii)[[2]]
      start_time <- Sys.time()
      Sys.sleep(sleep_time)
      list(sleep_time = sleep_time, 
           start_time = start_time,
           end_time = Sys.time(), 
           pid = Sys.getpid())
    })
  }
  v <- lapply(f, FUN = value)
  bind_rows(v)
}
data<- sleep_times
# 4x faster for multiprocess on MBP
res10x <- microbenchmark::microbenchmark(
  eager_bm(data),
  multiprocess_bm(data),
  times=10L
)