parallel_start: Start parallel clusters / plans

In modeltime: The Tidymodels Extension for Time Series Modeling

Start parallel clusters / plans

Description

Start parallel clusters / plans

Usage

parallel_start(
  ...,
  .method = c("parallel", "spark", "future"),
  .export_vars = NULL,
  .packages = NULL
)

parallel_stop()

Arguments

...	Parameters passed to underlying functions (See Details Section)
.method	The method to create the parallel backend. Supports: "future" - Uses the future package; foreach bridged via doFuture "parallel" - Uses the parallel + doParallel packages "spark" - Uses the sparklyr package
.export_vars	Environment variables that can be sent to the workers (not needed for "future")
.packages	Packages that can be sent to the workers (auto-handled by "future")

Details

future (.method = "future")

Sets a future::multisession plan (portable across OSes) and registers a foreach backend via doFuture::registerDoFuture(). This avoids the tune foreach/future warning.

• Pass the first unnamed ... argument as worker count (numeric) or omit to default to parallelly::availableCores(logical = FALSE) or 2 if unknown.

parallel (.method = "parallel")

1. parallel::makeCluster(...) 2) doParallel::registerDoParallel(cl)

2. Set .libPaths() on workers; optional clusterExport and package loads.

spark (.method = "spark")

Requires sparklyr::spark_connect(); registers foreach via sparklyr::registerDoSpark(...).

Examples

# Starts 2 clusters
parallel_start(2)

# Returns to sequential processing
parallel_stop()

modeltime documentation built on Dec. 17, 2025, 9:07 a.m.