az_rec_service {SAR} | R Documentation |
Azure product recommendations service class
Description
Class representing an Azure product recommendations service.
Format
An R6 object of class az_rec_service
, inheriting from AzureRMR::az_template
.
Methods
-
new(token, subscription, resource_group, name, ...)
: Initialize a recommendations service object. See 'Initialization' for more details. -
start()
: Start the service. -
stop()
: Stop the service. -
get_rec_endpoint()
: Return an object representing the client endpoint for the service. -
set_data_container(data_container="inputdata")
: sets the name of the blob container to use for storing datasets. -
delete(confirm=TRUE)
: Delete the service, after checking for confirmation.
Initialization
Generally, the easiest way to initialize a new recommendations service object is via the create_rec_service
or get_rec_service
methods of the az_subscription or az_resource_group classes.
To create a new recommendations service, supply the following additional arguments to new()
:
-
hosting_plan
: The name of the hosting plan (essentially the size of the virtual machine on which to run the service). See below for the plans that are available. -
storage_type
: The type of storage account to use. Can be"Standard_LRS"
or"Standard_GRS"
. -
insights_location
: The location for the application insights service. Defaults to"East US"
. -
data_container
: The default blob storage container to use for saving input datasets. Defaults to"inputdata"
. -
wait
: Whether to wait until the service has finished provisioning. Defaults to TRUE.
See Also
rec_endpoint, for the client interface to the recommendations service
Deployment instructions at the Product Recommendations API repo on GitHub
Examples
## Not run:
# recommended way of retrieving a resource: via a resource group object
svc <- resgroup$get_rec_service("myrec")
# start the service backend
svc$start()
# get the service endpoint
rec_endp <- svc$get_rec_endpoint()
## End(Not run)