makeClusterFunctionsInteractive: ClusterFunctions for Sequential Execution in the Running R...
In mllg/batchtools: Tools for Computation on Batch Systems

View source: R/clusterFunctionsInteractive.R

makeClusterFunctionsInteractive

R Documentation

ClusterFunctions for Sequential Execution in the Running R Session

Description

All jobs are executed sequentially using the current R process in which submitJobs is called. Thus, submitJob blocks the session until the job has finished. The main use of this ClusterFunctions implementation is to test and debug programs on a local computer.

Listing jobs returns an empty vector (as no jobs can be running when you call this) and killJob is not implemented for the same reasons.

Usage

makeClusterFunctionsInteractive(
  external = FALSE,
  write.logs = TRUE,
  fs.latency = 0
)

Arguments

`external`	[`logical(1)`] If set to `TRUE`, jobs are started in a fresh R session instead of currently active but still waits for its termination. Default is `FALSE`.
`write.logs`	[`logical(1)`] Sink the output to log files. Turning logging off can increase the speed of calculations but makes it very difficult to debug. Default is `TRUE`.
`fs.latency`	[`numeric(1)`] Expected maximum latency of the file system, in seconds. Set to a positive number for network file systems like NFS which enables more robust (but also more expensive) mechanisms to access files and directories. Usually safe to set to `0` to disable the heuristic, e.g. if you are working on a local file system.

Value

[ClusterFunctions].

Other ClusterFunctions: makeClusterFunctionsDocker(), makeClusterFunctionsLSF(), makeClusterFunctionsMulticore(), makeClusterFunctionsOpenLava(), makeClusterFunctionsSGE(), makeClusterFunctionsSSH(), makeClusterFunctionsSlurm(), makeClusterFunctionsSocket(), makeClusterFunctionsTORQUE(), makeClusterFunctions()