future_map2: Map over multiple inputs simultaneously via futures

In furrr: Apply Mapping Functions in Parallel using Futures

Map over multiple inputs simultaneously via futures

Description

These functions work the same as purrr::map2() and its variants, but allow you to map in parallel. Note that "parallel" as described in purrr is just saying that you are working with multiple inputs, and parallel in this case means that you can work on multiple inputs and process them all in parallel as well.

Usage

future_map2(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_chr(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_dbl(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_int(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_lgl(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_vec(
  .x,
  .y,
  .f,
  ...,
  .ptype = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_dfr(
  .x,
  .y,
  .f,
  ...,
  .id = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_dfc(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_chr(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_dbl(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_int(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_lgl(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_vec(
  .l,
  .f,
  ...,
  .ptype = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_dfr(
  .l,
  .f,
  ...,
  .id = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_dfc(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_walk2(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pwalk(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

Arguments

.x, .y	A pair of vectors, usually the same length. If not, a vector of length 1 will be recycled to the length of the other.
.f	A function, specified in one of the following ways: A named function. An anonymous function, e.g. ⁠\(x, y) x + y⁠ or function(x, y) x + y. A formula, e.g. ~ .x + .y. Use .x to refer to the current element of x and .y to refer to the current element of y. No longer recommended.
...	Additional arguments passed on to the mapped function. We now generally recommend against using ... to pass additional (constant) arguments to .f. Instead use a shorthand anonymous function: # Instead of x |> future_map(f, 1, 2, collapse = ",") # do: x |> future_map(\(x) f(x, 1, 2, collapse = ",")) This makes it easier to understand which arguments belong to which function and will tend to yield better error messages.
.options	The future specific options to use with the workers. This must be the result from a call to furrr_options().
.env_globals	The environment to look for globals required by .x and .... Globals required by .f are looked up in the function environment of .f.
.progress	A single logical. Should a progress bar be displayed? Only works with multisession, multicore, and multiprocess futures. Note that if a multicore/multisession future falls back to sequential, then a progress bar will not be displayed. Warning: The .progress argument will be deprecated and removed in a future version of furrr in favor of using the more robust progressr package.
.ptype	If NULL, the default, the output type is the common type of the elements of the result. Otherwise, supply a "prototype" giving the desired type of output.
.id	Either a string or NULL. If a string, the output will contain a variable with that name, storing either the name (if .x is named) or the index (if .x is unnamed) of the input. If NULL, the default, no variable will be created. Only applies to ⁠_dfr⁠ variant.
.l	A list of vectors. The length of .l determines the number of arguments that .f will be called with. Arguments will be supply by position if unnamed, and by name if named. Vectors of length 1 will be recycled to any length; all other elements must be have the same length. A data frame is an important special case of .l. It will cause .f to be called once for each row.

Value

An atomic vector, list, or data frame, depending on the suffix. Atomic vectors and lists will be named if .x or the first element of .l is named.

If all input is length 0, the output will be length 0. If any input is length 1, it will be recycled to the length of the longest.

Examples

plan(multisession, workers = 2)

x <- list(1, 10, 100)
y <- list(1, 2, 3)
z <- list(5, 50, 500)

future_map2(x, y, ~ .x + .y)

# Split into pieces, fit model to each piece, then predict
by_cyl <- split(mtcars, mtcars$cyl)
mods <- future_map(by_cyl, ~ lm(mpg ~ wt, data = .))
future_map2(mods, by_cyl, predict)

future_pmap(list(x, y, z), sum)

# Matching arguments by position
future_pmap(list(x, y, z), function(a, b ,c) a / (b + c))

# Vectorizing a function over multiple arguments
df <- data.frame(
  x = c("apple", "banana", "cherry"),
  pattern = c("p", "n", "h"),
  replacement = c("x", "f", "q"),
  stringsAsFactors = FALSE
)

future_pmap(df, gsub)
future_pmap_chr(df, gsub)

furrr documentation built on March 31, 2026, 5:06 p.m.