mirai Map

Asynchronous parallel map of a function over a list or vector using mirai, with optional promises integration. Performs multiple map over the rows of a dataframe or matrix.

Usage

mirai_map(.x, .f, ..., .args = list(), .promise = NULL, .compute = "default")

Arguments

.x

a list or atomic vector. Also accepts a matrix or dataframe, in which case multiple map is performed over its rows.

.f

a function to be applied to each element of .x, or row of .x as the case may be.

...

(optional) named arguments (name = value pairs) specifying objects referenced, but not defined, in .f.

.args

(optional) further constant arguments to .f, provided as a list.

.promise

(optional) if supplied, registers a promise against each mirai. Either a function, supplied to the ‘onFulfilled’ argument of promises::then() or a list of 2 functions, supplied respectively to ‘onFulfilled’ and ‘onRejected’ for promises::then(). Using this argument requires the promises package.

.compute

[default 'default'] character value for the compute profile to use (each compute profile has its own independent set of daemons).

Value

A ‘mirai_map’ (list of ‘mirai’ objects).

Details

Sends each application of function .f on an element of .x (or row of .x) for computation in a separate mirai call.

This simple and transparent behaviour is designed to make full use of mirai scheduling to minimise overall execution time.

Facilitates recovery from partial failure by returning all ‘miraiError’ / ‘errorValue’ as the case may be, thus allowing only the failures to be re-run.

Note: requires daemons to have previously been set. If not, then one local daemon is set before the function propceeds.

Results

x[] collects the results of a ‘mirai_map’ x and returns a list. This will wait for all asynchronous operations to complete if still in progress, blocking but user-interruptible.

x[.flat] collects and flattens map results to a vector, checking that they are of the same type to avoid coercion. Note: errors if an ‘errorValue’ has been returned or results are of differing type.

x[.progress] collects map results whilst showing a simple text progress indicator of parts completed of the total.

x[.progress_cli] collects map results whilst showing a progress bar from the cli package, if available, with completion percentage and ETA.

x[.stop] collects map results applying early stopping, which stops at the first failure and cancels remaining operations. Note: operations already in progress continue to completion, although their results are not collected.

The options above may be combined in the manner of:
x[.stop, .progress] which applies early stopping together with a progress indicator.

Multiple Map

Multiple map is performed automatically over the rows of an object with ‘dim’ attributes such as a matrix or dataframe. This is most often the desired behaviour.

To map over columns instead, first wrap a dataframe in as.list, or transpose a matrix using t.

Examples

if (interactive()) {
# Only run examples in interactive R sessions

daemons(4, dispatcher = "none")

# map with constant args specified via '.args'
mirai_map(1:3, rnorm, .args = list(mean = 20, sd = 2))[]

# flatmap with function definition passed via '...'
mirai_map(1:3, function(x) func(1L, x, x + 1L), func = stats::runif)[.flat]

# sum rows of a dataframe
(df <- data.frame(a = 1:3, b = c(4, 3, 2)))
mirai_map(df, sum)[.flat]

# sum rows of a matrix
(mat <- matrix(1:4, nrow = 2L))
mirai_map(mat, sum)[.flat]

# map over rows of a dataframe
df <- data.frame(a = c("Aa", "Bb"), b = c(1L, 4L))
mirai_map(df, function(...) sprintf("%s: %d", ...))[.flat]

# indexed map over a vector
v <- c("egg", "got", "ten", "nap", "pie")
mirai_map(
  data.frame(1:length(v), v),
  sprintf,
  .args = list(fmt = "%d_%s")
)[.flat]

# return a 'mirai_map' object, check for resolution, collect later
mp <- mirai_map(
  c(a = 2, b = 3, c = 4),
  function(x, y) do(x, as.logical(x %% y)),
  do = nanonext::random,
  .args = list(y = 2)
)
unresolved(mp)
mp
mp[]
unresolved(mp)

# progress indicator counts up from 0 to 4 seconds
res <- mirai_map(1:4, Sys.sleep)[.progress]

daemons(0)

# generates warning as daemons not set
# stops early when second element returns an error
tryCatch(
  mirai_map(list(1, "a", 3), sum)[.stop],
  error = identity
)

# promises example that outputs the results, including errors, to the console
if (requireNamespace("promises", quietly = TRUE)) {
daemons(1, dispatcher = "none")
ml <- mirai_map(
  1:30,
  function(x) {Sys.sleep(0.1); if (x == 30) stop(x) else x},
  .promise = list(
    function(x) cat(paste(x, "")),
    function(x) { cat(conditionMessage(x), "\n"); daemons(0) }
  )
)
}

}