Does fable package ARIMA algorithm able to work parallel?

Question

I am trying to create forecasts for 1000 stores using fable package. Does fable package has work in parallel like the forecast function did?

Thank you very much

Answer 1

You can parallelise the fitting of a model using plan() from the future package.

It is possible to estimate models in parallel using the future package. By specifying a future::plan() before estimating the models, they will be computed according to that plan.

https://fabletools.tidyverts.org/reference/model.html

library(fable)
#> Loading required package: fabletools
library(dplyr)
library(future)

plan(multisession)

tsibbledata::aus_retail %>%
  filter(
    Industry == "Food retailing"
  ) %>%
  model(
    snaive = SNAIVE(Turnover),
    ets = ETS(log(Turnover) ~ error("A") + trend("A") + season("A")),
  )
#> # A mable: 8 x 4
#> # Key:     State, Industry [8]
#>   State                        Industry         snaive          ets
#>   <chr>                        <chr>           <model>      <model>
#> 1 Australian Capital Territory Food retailing <SNAIVE> <ETS(A,A,A)>
#> 2 New South Wales              Food retailing <SNAIVE> <ETS(A,A,A)>
#> 3 Northern Territory           Food retailing <SNAIVE> <ETS(A,A,A)>
#> 4 Queensland                   Food retailing <SNAIVE> <ETS(A,A,A)>
#> 5 South Australia              Food retailing <SNAIVE> <ETS(A,A,A)>
#> 6 Tasmania                     Food retailing <SNAIVE> <ETS(A,A,A)>
#> 7 Victoria                     Food retailing <SNAIVE> <ETS(A,A,A)>
#> 8 Western Australia            Food retailing <SNAIVE> <ETS(A,A,A)>

^{Created on 2020-11-23 by the reprex package (v0.3.0)}