rrq_task_create_call: Create a task from a call
In mrc-ide/rrq: Simple Redis Queue

rrq_task_create_call

R Documentation

Create a task from a call

Description

Create a task based on a function call. This is fairly similar to callr::r, and forms the basis of lapply()-like task submission. Sending a call may have slightly different semantics than you expect if you send a closure (a function that binds data), and we may change behaviour here until we find a happy set of compromises. See Details for more on this. The expression rrq_task_create_call(f, list(a, b, c)) is similar to rrq_task_create_expr(f(a, b, c)), use whichever you prefer.

Usage

rrq_task_create_call(
  fn,
  args,
  queue = NULL,
  separate_process = FALSE,
  timeout_task_run = NULL,
  depends_on = NULL,
  controller = NULL
)

Arguments

`fn`	The function to call
`args`	A list of arguments to pass to the function
`queue`	The queue to add the task to; if not specified the "default" queue (which all workers listen to) will be used. If you have configured workers to listen to more than one queue you can specify that here. Be warned that if you push jobs onto a queue with no worker, it will queue forever.
`separate_process`	Logical, indicating if the task should be run in a separate process on the worker. If `TRUE`, then the worker runs the task in a separate process using the `callr` package. This means that the worker environment is completely clean, subsequent runs are not affected by preceding ones. The downside of this approach is a considerable overhead in starting the external process and transferring data back.
`timeout_task_run`	Optionally, a maximum allowed running time, in seconds. This parameter only has an effect if `separate_process` is `TRUE`. If given, then if the task takes longer than this time it will be stopped and the task status set to `TIMEOUT`.
`depends_on`	Vector or list of IDs of tasks which must have completed before this job can be run. Once all dependent tasks have been successfully run, this task will get added to the queue. If the dependent task fails then this task will be removed from the queue.
`controller`	The controller to use. If not given (or `NULL`) we'll use the controller registered with `rrq_default_controller_set()`.

Details

Things are pretty unambiguous when you pass in a function from a package, especially when you refer to that package with its namespace (e.g. pkg::fn).

If you pass in the name without a namespace from a package that you have loaded with library() locally but you have not loaded with library within your worker environment, we may not do the right thing and you may see your task fail, or find a different function with the same name.

If you pass in an anonymous function (e.g., function(x) x + 1) we may or may not do the right thing with respect to environment capture. We never capture the global environment so if your function is a closure that tries to bind a symbol from the global environment it will not work. Like with callr::r, anonymous functions will be easiest to think about where they are fully self contained (i.e., all inputs to the functions come through args). If you have bound a local environment, we may do slightly better, but semantics here are undefined and subject to change.

R does some fancy things with function calls that we don't try to replicate. In particular you may have noticed that this works:

c <- "x"
c(c, c) # a vector of two "x"'s

You can end up in this situation locally with:

f <- function(x) x + 1
local({
  f <- 1
  f(f) # 2
})

this is because when R looks for the symbol for the call it skips over non-function objects. We don't reconstruct environment chains in exactly the same way as you would have locally so this is not possible.