Batch deployment input details for R scripts in Watson Machine Learning

Data Sources

Input/output data references:

• Local/managed assets from the space
• Connected (remote) assets: Cloud Object Storage and Storage Volumes

Notes:

• For connections of type Cloud Object Storage or Cloud Object Storage (infrastructure), you must configure Access key and Secret key, also known as HMAC credentials.

If you are specifying input/output data references programmatically:

• Data source reference type depends on the asset type. Refer to the Data source reference types section in Adding data assets to a deployment space.
• You can specify environment variables that are required for executing the R Script as 'key': 'value' pairs in scoring.environment_variables. The key must be the name of an environment variable and the value must be the corresponding value of the environment variable.
• The deployment job's payload will be saved as a JSON file in the deployment container where the R script will be executed. The R script can access the full path file name of the JSON file by using the JOBS_PAYLOAD_FILE environment variable.
• If input data is referenced as a local or managed data asset, deployment service will download the input data and place it in the deployment container where the R script will be executed. You can access the location (path) of the downloaded input data through the BATCH_INPUT_DIR environment variable.
• For input data references (data asset or connection asset), downloading of the data must be handled by the R script. If a connected data asset or a connection asset is present in the deployment jobs payload, you can access it using the JOBS_PAYLOAD_FILE environment variable that contains the full path to deployment job's payload saved as a JSON file.
• If output data must be persisted as a local or managed data asset in a space, you can specify the name of the asset to be created in scoring.output_data_reference.location.name. As part of R script, output data can be placed in the path that is specified by the BATCH_OUTPUT_DIR environment variable. Deployment service will compress the data to .zip format and upload it in the location that is specified in BATCH_OUTPUT_DIR.
• If output data must be saved in a remote data store, you must specify the reference of the output data reference (for example, a data asset or a connected data asset) in output_data_reference.location.href. The R script must take care of uploading the output data to the remote data source. If a connected data asset or a connection asset reference is present in the deployment jobs payload, you can access it using the JOBS_PAYLOAD_FILE environment variable that contains the full path to deployment job's payload saved as a JSON file.
• If the R script does not require any input or output data references to be specified in the deployment job payload, then do not provide the scoring.input_data_references and scoring.output_data_references objects in the payload.
• R Scripts are currently supported only with the default software spec default_r3.6; specifying a custom software specification is not supported.
• Deploying a script to run on a Hadoop environment is currently not supported.

Parent topic: Batch deployment input details by framework