Description Usage Arguments Details Value References
Remote execution of R script in an R interface new_interface.
1 2 3 | executeScript(context, resource.group, hostname, remote, username, script,
master = "", slaves = "", compute.context = ifelse(master == "" &&
slaves == "", "localParallel", "clusterParallel"))
|
context |
Authentication context of AzureSMR encapsulating the TID, CID, and key obtained from Azure Actrive Directory. |
resource.group |
The Azure resource group where the DSVM is created. |
hostname |
Name of the DSVM. Lowercase characters or numbers only. Special characters are not permitted. |
remote |
IP address or FQDN for a computation engine. For DSVM, it is either the fully qualified domain name (usually in the format of <hostname>.<location>.cloudapp.azure.com) or its public IP address. Note if more than one machines are used for execution, the remote is used as master node by default. |
username |
User name of the DSVM. It should be different from 'name'. |
script |
R script to be executed on remote resource(s). |
master |
IP address or URL of a DSVM which will be used as the master. By default is remote. |
slaves |
IP addresses or URLs of slave DSVMs. |
compute.context |
Computation context of Microsoft R Server under which the mechanisms of parallelization (e.g., local parallel, cluster based parallel, etc.) is specified. Accepted computing context include "localSequential", "localParallel", and "clusterParallel". |
For a "localSequential" compute context, there is no parallelism and
the analytics run in a sequential manner. In the "localParallel"
compute context, the analytics will be run across available cores
of a computing node. The number of available cores can be checked with
Microsoft RevoScaleR function rxGetOption
. The "clusterParallel"
compute context enables parallel computation across coputing nodes of
a cluster.
Status of scription execution.
Details about distributed computing with Microsoft RevoScaleR package can be found at https://msdn.microsoft.com/en-us/microsoft-r/scaler-distributed-computing.
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