inst/doc/quickstart.R

In clustermq: Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)

## ----echo=FALSE, results="hide"-----------------------------------------------
options(clustermq.scheduler = "local")
knitr::opts_chunk$set(
    cache = FALSE,
    echo = TRUE,
    collapse = TRUE,
    comment = "#>"
)

## -----------------------------------------------------------------------------
# load the library and create a simple function
library(clustermq)
fx = function(x) x * 2

# queue the function call on your scheduler
Q(fx, x=1:3, n_jobs=1)

## ----eval=FALSE---------------------------------------------------------------
#  # install.packages('remotes')
#  remotes::install_github('mschubert/clustermq', ref="develop")

## -----------------------------------------------------------------------------
fx = function(x) x * 2
Q(fx, x=1:3, n_jobs=1)

## -----------------------------------------------------------------------------
fx = function(x, y) x * 2 + y
Q(fx, x=1:3, const=list(y=10), n_jobs=1)

## -----------------------------------------------------------------------------
fx = function(x) x * 2 + y
Q(fx, x=1:3, export=list(y=10), n_jobs=1)

## -----------------------------------------------------------------------------
fx = function(x) {
    `%>%` = dplyr::`%>%`
    x %>%
        dplyr::mutate(area = Sepal.Length * Sepal.Width) %>%
        head()
}
Q(fx, x=list(iris), n_jobs=1)

## -----------------------------------------------------------------------------
library(foreach)
register_dopar_cmq(n_jobs=2, memory=1024) # accepts same arguments as `workers`
foreach(i=1:3) %dopar% sqrt(i) # this will be executed as jobs

## ----eval=FALSE---------------------------------------------------------------
#  library(BiocParallel)
#  register(DoparParam()) # after register_dopar_cmq(...)
#  bplapply(1:3, sqrt)