Service {parabar} | R Documentation |
Service
Description
This is an interface that defines the operations available on a
Backend
implementation. Backend implementations and the
Context
class must implement this interface.
Methods
Public methods
Method new()
Create a new Service
object.
Usage
Service$new()
Returns
Instantiating this call will throw an error.
Method start()
Start the backend.
Usage
Service$start(specification)
Arguments
specification
An object of class
Specification
that contains the backend configuration.
Returns
This method returns void. The resulting backend must be stored in the
.cluster
private field on the Backend
abstract class,
and accessible to any concrete backend implementations via the active
binding cluster
.
Method stop()
Stop the backend.
Usage
Service$stop()
Returns
This method returns void.
Method clear()
Remove all objects from the backend. This function is equivalent to
calling rm(list = ls(all.names = TRUE))
on each node in the
backend.
Usage
Service$clear()
Details
This method is ran by default when the backend is started.
Returns
This method returns void.
Method peek()
Inspect the backend for variables available in the .GlobalEnv
.
Usage
Service$peek()
Returns
This method returns a list of character vectors, where each element
corresponds to a node in the backend. The character vectors contain
the names of the variables available in the .GlobalEnv
on each
node.
Method export()
Export variables from a given environment to the backend.
Usage
Service$export(variables, environment)
Arguments
variables
A character vector of variable names to export.
environment
An environment object from which to export the variables.
Returns
This method returns void.
Method evaluate()
Evaluate an arbitrary expression on the backend.
Usage
Service$evaluate(expression)
Arguments
expression
An unquoted expression to evaluate on the backend.
Returns
This method returns the result of the expression evaluation.
Method sapply()
Run a task on the backend akin to parallel::parSapply()
.
Usage
Service$sapply(x, fun, ...)
Arguments
x
An atomic vector or list to pass to the
fun
function.fun
A function to apply to each element of
x
....
Additional arguments to pass to the
fun
function.
Returns
This method returns void. The output of the task execution must be
stored in the private field .output
on the Backend
abstract class, and is accessible via the get_output()
method.
Method lapply()
Run a task on the backend akin to parallel::parLapply()
.
Usage
Service$lapply(x, fun, ...)
Arguments
x
An atomic vector or list to pass to the
fun
function.fun
A function to apply to each element of
x
....
Additional arguments to pass to the
fun
function.
Returns
This method returns void. The output of the task execution must be
stored in the private field .output
on the Backend
abstract class, and is accessible via the get_output()
method.
Method apply()
Run a task on the backend akin to parallel::parApply()
.
Usage
Service$apply(x, margin, fun, ...)
Arguments
x
An array to pass to the
fun
function.margin
A numeric vector indicating the dimensions of
x
thefun
function should be applied over. For example, for a matrix,margin = 1
indicates applyingfun
rows-wise,margin = 2
indicates applyingfun
columns-wise, andmargin = c(1, 2)
indicates applyingfun
element-wise. Named dimensions are also possible depending onx
. Seeparallel::parApply()
andbase::apply()
for more details.fun
A function to apply to
x
according to themargin
....
Additional arguments to pass to the
fun
function.
Returns
This method returns void. The output of the task execution must be
stored in the private field .output
on the Backend
abstract class, and is accessible via the get_output()
method.
Method get_output()
Get the output of the task execution.
Usage
Service$get_output(...)
Arguments
...
Additional optional arguments that may be used by concrete implementations.
Details
This method fetches the output of the task execution after calling
the sapply()
method. It returns the output and immediately removes
it from the backend. Therefore, subsequent calls to this method are
not advised. This method should be called after the execution of a
task.
Returns
A vector, matrix, or list of the same length as x
, containing the
results of the fun
. The output format differs based on the specific
operation employed. Check out the documentation for the apply
operations of parallel::parallel
for more information.
Method clone()
The objects of this class are cloneable with this method.
Usage
Service$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
See Also
Backend
, SyncBackend
, AsyncBackend
,
and Context
.