| az_rec_service | R Documentation |
Class representing an Azure product recommendations service.
An R6 object of class az_rec_service, inheriting from AzureRMR::az_template.
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.
Generally, the easiest way to initialize a new recommendations service object is via the create_rec_service or get_rec_service methods of the AzureRMR::az_subscription or AzureRMR::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.
rec_endpoint, for the client interface to the recommendations service
Deployment instructions at the Product Recommendations API repo on GitHub
## 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)
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